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The Complete Excel, ChatGPT, AI Online Course Mega Bundle
LEVEL 1 🚀👨💻 Excel for Beginners
Source Files
01 Quick Win - Track Spendings And Savings In Excel (9:58)
02 Make Your Expense Tracker More Readable (5:54)
Excel Functions Mastery Course
Source Files
1.1 Introduction to the Course (8:47)
1.2 Introduction of the instructor (3:30)
1.3 Course requirements (4:04)
1.4 How to get Excel (9:33)
2.1 What will we learn in this section (1:33)
2.2 Create An If() Function (3:24)
2.3 Nest And() Andor Or() Functions Within Reference Functions (6:37)
2.4 Work With Choose(), Vlookup(), Index(), And Match() Functions (6:19)
2.5 Create A Vlookup() Function (3:32)
2.6 Section Summary (9:37)
3.1 What will we learn in this section (2:23)
3.2 Aggregate Data Using Both The Sum And Subtotal Functions (5:15)
3.3 Calculate minimums, maximums and averages from data sets (3:39)
3.4 Use the Forecast function to forecast numbers along a trend (6:57)
3.5 Generate a net present value using a formula (6:13)
3.6 Section Summary (7:38)
4.1 What will we learn in this section (1:14)
4.2 Work with Excel’s date manipulation functions (10:10)
4.3 Build a holiday date calculator (6:09)
4.4 Section Summary (4:43)
5.1 What will we learn in this section (3:46)
5.2 Split textual data apart (4:00)
5.3 Manipulate textual data (5:47)
5.4 Replace portions of textual data (4:42)
5.5 Put textual data back together with formulae (6:18)
5.6 Work with key informational functions for evaluating and responding correctly to errors in routine Excel calculations (12:00)
5.7 Use the Hyperlink function to build navigational menus inside an Excel Worksheet (4:35)
5.8 Section Summary (6:26)
6.1 What will we learn in this section (4:08)
6.2 How to filter items in a list (8:24)
6.3 Sorting List without messing up the data (10:09)
6.4 How to freeze rows or columns (9:53)
6.5 Remove duplicates from a list (6:52)
6.6 Section Summary (6:32)
7.1 What will we learn in this section (2:09)
7.2 COUNT, COUNTA and COUNTIF Functions (11:57)
7.3 Create a drop down list (11:38)
7.4 Work with ISNUMBER and SEARCH functions within text functions (11:19)
7.5 Format row based on a cell value (10:54)
7.6 Create an invoice template in Excel (24:17)
7.7 Section Summary (4:46)
8.1 Course Summary and Next Steps (23:32)
LEVEL 2 🧙♂️🎩 Advanced Excel Functions - Introduction to PivotTables in Excel
Source Files
1.1 Introduction To The Course New (3:43)
1.2 Why Should You Learn Pivottables New (3:17)
1.3 Introduction Of The Instructor New (3:17)
1.4 Course Requirements (what Software, Experience) New (6:10)
2.1 What We Learn In This Section (1:21)
2.2 What Is A Pivot Table (2:01)
2.3 Pivottables Basics (2:52)
2.4 Pivottable Compliant Data Sources (2:12)
2.5 Build A Basic Pivottable (4:17)
2.6 Section Summary (2:13)
2.7 Challenge (1:23)
3.1 What Will We Learn In This Section (1:01)
3.2 Introduction To Formatting Pivottables (3:30)
3.3 Build An Expense Report (6:03)
3.4 Format The Expense Report Pivottable (4:18)
3.5 Finalize The Expense Report Pivottable (5:41)
3.6 Section Summary (2:12)
3.7 Challenge (1:04)
4.1 What Will We Learn In This Section (8:46)
4.2 What Are Excel Tables (7:23)
4.3 Sales Report Analysis With Pivottables (9:22)
4.4 Modify Source Data (3:58)
4.5 Format The Sales Report (8:38)
4.6 Complete The Sales Report Analysis (3:38)
4.7 Section Summary (3:03)
4.8 Challenge (1:47)
5.1 What Will We Learn In This Section (1:23)
5.2 What Is Slicing Data (3:41)
5.3 Slicing Data Project (5:40)
5.4 Data Slicer Tools (14:09)
5.5 Link Slicers To Multiple Pivottables (8:03)
5.6 Section Summary (2:32)
5.7 Challenge (2:04)
6.1 What Will We Learn In This Section (2:30)
6.2 Connect To Databases (2:06)
6.3 Import Data Sources (3:58)
6.4 Use Pivottables To Refine Data (4:41)
6.5 Consolidate Your Data Table (3:17)
6.6 Format Large Data Sets (4:51)
6.7 Slicer And Timeline In Large Data Sets (4:36)
6.8 Refresh And Drill Down From Databases (4:46)
6.9 Section Summary (4:01)
6.10 Challenge (2:02)
Excel Charts and Visualization
1.1 Introduction To The Course (4:46)
1.2 Why Should You Learn About Charts And Data Visualization (4:31)
1.3 Introduction Of The Instructor (2:08)
1.4 Course Requirements (what Software, Experience) (2:36)
2.1 What Will We Learn In This Section (1:21)
2.2 Main Principles And Chart Visualization Impact (2:39)
2.3 Choosing The Correct Chart (1:56)
2.4 Communicate With The End User (2:18)
2.5 Section Summary (2:59)
2.6 Challenge (2:12)
3.1 What Will We Learn In This Section (1:36)
3.2 Chart Design (6:39)
3.3 Working With Chart Formats (4:35)
3.4 Chart Types (2:08)
3.5 Primary & Secondary Axis (4:20)
3.6 Chart Templates (3:25)
3.7 Section Summary (2:50)
3.8 Challenge (1:23)
Excel Charts and Visualization (Part 2)
4.1 What Will We Learn In This Section (1:20)
4.2 Excel Column Charts (4:13)
4.3 Column Charts Challenge (1:08)
4.4 Excel Bar Charts (3:12)
4.5 Bar Charts Challenge (0:48)
4.6 Excel Line Charts (3:52)
4.7 Line Charts Challenge (0:48)
4.8 Excel Pie Charts (5:01)
4.9 Pie Charts Challenge (0:57)
4.10 Excel Area Charts (2:27)
4.11 Area Charts Challenge (0:50)
4.12 Excel Scatter Charts (4:00)
4.13 Scatter Charts Challenge (0:41)
4.14 Excel Bubble Charts (5:12)
4.15 Bubble Charts Challenge (0:54)
4.16 Excel Stock Charts (3:07)
4.17 Stock Charts Challenge (0:56)
4.18 Excel Surface Charts (4:42)
4.19 Surface Charts Challenge (0:43)
4.20 Excel Radar Charts (2:58)
4.21 Radar Charts Challenge (0:38)
4.22 Excel Treemap Charts (2:31)
4.23 Treemap Charts Challenge (1:03)
4.24 Excel Sunburst Charts (2:36)
4.25 Sunburst Charts Challenge (0:59)
4.26 Excel Histogram & Pareto Charts (4:02)
4.27 Histogram & Pareto Charts Challenge (1:04)
4.28 Excel Waterfall Charts (5:26)
4.29 Waterfall Charts Challenge (0:46)
4.30 Excel Box & whisker Charts (3:24)
4.31 Box & whisker Charts Challenge (1:03)
4.32 Excel Sparklines (3:44)
4.33 Sparklines Challenge (0:53)
4.34 Excel Color Scales (3:42)
4.35 Color Scales Challenge (0:49)
4.36 Excel 3d Map (4:35)
4.37 3D Map Challenge (1:45)
4.38 Section Summary (10:13)
Excel Charts and Visualization (Part 3)
5.1 What Will We Learn In This Section (2:23)
5.2 Data Visualization With Pivot Chart And Slicers (7:05)
5.3 Challenge Data Visualization With Pivot Chart And Slicers (1:34)
5.4 Create Break Even Chart (9:25)
5.5 Challenge Break Even Chart (1:12)
5.6 Rating Star Chart (7:09)
5.7 Challenge Star Rating (1:28)
5.8 Drop Down Menu For Chart (16:31)
5.9 Challenge Drop Down Menu Chart (1:20)
5.10 Risk Score Chart (11:03)
5.11 Challenge Risk Score Chart (1:23)
5.12 Dynamic Chart Update (8:10)
5.13 Challenge Dynamic Chart Update (1:47)
5.14 Section Summar (6:48)
6.1 Course Summary And Next Steps (16:29)
Excel Financial Analysis
1.1 Introduction To The Course (4:16)
1.2 Why Should You Learn Financial Analysis (4:22)
1.3 Introduction Of The Instructor (6:24)
1.4 Course Requirements (what Software, Experience) (5:46)
2.1 What Will We Learn In This Section (2:35)
2.2 Preparing Data Source For P&l (16:08)
2.3 Create P&l Structure (13:27)
2.4 Adding Data To P&l (19:48)
2.5 Calculating Variances (11:51)
2.6 Balance Sheet Structure (10:43)
2.7 Adding Values On Bs From Different Files Format (20:38)
2.8 Cash Flow Structure (10:25)
2.9 Calculating Cash Flow (11:05)
2.10 Challenge (1:36)
3.1 What Will We Learn In This Section (5:48)
3.2 Forecast With Scenarios (23:30)
3.3 How To Calculate Finance Main KPI-s (15:38)
3.4 Fixed Assets Roll Forward (18:29)
3.5 Loan Schedule (13:54)
3.6 Ar Management Basics (20:49)
3.7 Customers Rank (11:56)
3.8 Create Budgets Categories (19:45)
3.9 Challenge (1:25)
4.1 Course Summary And Next Steps (31:21)
Excel Data Visualization
1.1 Introduction To The Course (8:27)
Source Files
1.2 Introduction Of The Instructor (3:11)
1.3 Course Requirements (2:59)
1.4 How To Get Excel (4:14)
2.1 What Will We Learn In This Section (1:20)
2.2 What Are Dashboards (5:39)
2.3 Answers You Need Before You Start A Dashboard (7:45)
2.4 Best Practices For Dashboard Layout (4:42)
2.5 Best Practices For Dashboard Colors (3:54)
2.6 Section Summary (3:40)
3.1 What will we learn in this section (1:16)
3.2 Build a Wireframe in Excel (5:42)
3.3 Prepare Raw Data for Dashboard (5:57)
3.4 Prepare Calculation sheet (13:01)
3.5 Section Summary (6:08)
4.1 What will we learn in this section (2:48)
4.2 Build a Combo Box (10:44)
4.3 Complex Lookup (14:36)
4.4 Build a Scrolling Data Table (11:41)
4.5 Conditionally Format Actual Values vs Budgeted Values (10:52)
4.6 Conditional Headers (9:25)
4.7 Section Summary (3:01)
5.1 What will we learn in this section (1:50)
5.2 Show Top Matches Over and Under Budget (9:21)
5.3 List Box to Select Indicators (5:11)
5.4 Toggle Between Top Over or Under (12:50)
5.5 Section Summary (2:19)
6.1 What will we learn in this section (3:20)
6.2 Prepare Data for Scrolling Chart (14:19)
6.3 Scrollable Line Chart (11:17)
6.4 Remove Crashing Lines (4:13)
6.5 Toggle Visibility of Line Series (9:56)
6.6 Finetune the Line Series (7:08)
6.7 Section Summary (5:35)
7.1 What will we learn in this section (1:56)
7.2 Add Interactivity to Reports with Pivot Slicers (10:44)
7.3 Column Chart Controlled by Slicer (6:47)
7.4 Pivot SLicer Sorting (4:26)
7.5 Select Only 1 Slicer (2:13)
7.6 Dynamic Comments with SLicers (11:36)
7.7 Section Summary (2:58)
8.1 What will we learn in this section (1:01)
8.2 Add Calculations for Variances in Pivot Tables (4:23)
8.3 Conditional Formatting in Pivot Tables (7:04)
8.4 Refresh Pivot Table with Easy VBA (7:49)
8.5 Section Summary (2:33)
9.1 Course Summary and Next Steps (10:27)
Beginners Excel Power Query and M Masterclass - 01 Course Overview
Source Files 01
01 What Are Power Query And M (8:16)
02 Course Overview (6:16)
02 Build your first M queries
Source Files 02
01 Capitalize A Table Column (6:39)
02 Build An Expression With Let (17:10)
03 Join tables with M
01 Build And Reference Tables (8:08)
02 Append And Combine Tables (5:33)
03 Inner Join Tables (5:33)
Join tables with M - Source Files
04 Build M functions to perform tasks
01 Build M Functions To Perform Tasks (8:14)
02 Call Functions (5:10)
03 Use The Each Keyword (2:33)
04 Change A Table With A Function (7:30)
05 Loop An Action With A Recursive Function (8:02)
06 Calculate Price After Discount (6:09)
07 Use Optional Parameters To Combine Text (5:13)
08 Transform A List With A Function (2:09)
09 Calculate Number Of Working Days (12:20)
Build M functions to perform tasks - Source Files
05 Work with lists in M
01 Build A List With Each (5:16)
02 Concatenate Items In A List (5:01)
03 Iterate Over A List (4:18)
04 Iterate Over A List With Recursion (3:26)
Work with lists in M - Source Files
06 Build M variables to store data
01 Calculate Affiliate Revenue (4:37)
02 Variable Types (5:49)
03 Variable Scope - Where Can You Use Variables (8:57)
04 Order Of Evaluation (5:18)
Build M variables to store data - Source Files
07 Aggregate table data with M
01 Count Rows (7:32)
02 Calculate Profits Per Quarter (5:55)
03 Group Similar Rows (5:59)
04 Sort A Table (5:27)
05 Query Data From Another Spreadsheet (7:18)
06 Find Where Sales Met Quota (2:55)
Aggregate table data with M - Source Files
08 Work with tables in M
01 Build Tables (6:55)
02 Work With Tables (5:37)
03 Fill In A Table (3:27)
Work with tables in M - Source Files
09 Build conditions with M if expressions
01 Build Conditions With If Expressions (8:14)
Build conditions with M if expressions - Source Files
10 Work with M data types
01 Manipulate Text (11:34)
02 Work With Numbers (3:00)
03 Work With Date, Time And Duration (7:52)
Work with M data types - Source Files
11 Build queries for tables with M
01 Filter A Table By Row (6:59)
02 Format A List Of Values Into A Table (7:57)
Build queries for tables with M - Source Files
12 Build calculations for tables with M
01 Build Address Labels (8:27)
02 Calculate Percentage Of Total (6:44)
03 Calculate Sales Rank (7:04)
04 Count Number Of Distinct Rows (6:59)
Build calculations for tables with M - Source Files
13 Fetch data from the web with M
01 Query Tables From The Web (7:15)
02 Search For Links On The Web (8:09)
03 Check If A Webpage Exists (6:24)
Fetch data from various sources with M - Source Files
Advanced Excel Power Query and M Masterclass - 00 Course overview
00 Course Overview - Advanced Excel Power Query And M (4:09)
01 What Are Power Query And M (8:15)
Course overview - Source Files
01 Build expressions with let
01 Build Nested Let Expressions (3:53)
02 Build A List With A Sequence (2:43)
03 Build An Unnamed Record (4:14)
Build expressions with let - Source Files
02 Build expressions with each
01 Work With The Each Keyword (5:00)
02 Generate A List (5:41)
03 Find An Entry In A Record (2:16)
04 Select Items From A List (5:06)
05 Serialize A Column (13:43)
06 Find Best Match Of Values (21:49)
Build expressions with each - Source Files
03 Build M functions to perform tasks
01 Build A Function (3:21)
02 Build A Closure (6:27)
03 Build A Function In A Record (4:23)
04 Count Fibonacci Numbers With A Recursive Function (7:04)
05 Remove Html Tags (9:19)
06 Build A For Each Loop (9:38)
Build M functions to perform tasks - Source Files
04 Work with tables in M
01 Select A Column From A Table (3:40)
02 Select A Value At A Row And Column (3:05)
03 Select Row Where A Condition Is Met (3:53)
04 Cross Join Tables (8:40)
05 Join Tables On A Key (5:48)
06 Change Column Types (3:49)
07 Fill A Table With Random Values (7:12)
Work with tables in M - Source Files
05 Pivot a table
00 What Is Pivoting (1:28)
01 Pivot A Table (12:05)
Pivot a table - Source Files
06 Build expressions with evaluate
01 Build An Expression With Evaluate (3:06)
02 Build A Nested Evaluate Expression (3:04)
03 Use Global Library Functions (2:27)
Build expressions with evaluate - Source Files
07 Work with matrices in M
00 How To Multiply Matrices (3:03)
01 Build Matrices In M (4:32)
02 Multiply Matrics (17:45)
Work with matrices in M - Source Files
LEVEL 3 🤖🔮 Excel VBA & Macros
01.00 Course Overview (2:24)
02.00 How To Save Macros (1:34)
Source Files
Send Messages with MsgBox
03.00 Topics Overview (0:54)
03.01 Build A Simple Message (3:34)
03.02 Build An Advanced Message (5:10)
03.03 Empty A Sheet With The Msgbox Function (6:44)
03.04 Prompt User For Input (7:30)
03 Source Files
04 Workbook and Worksheet Object
04.00 Topics Overview (1:30)
04.01 Object Hierarchymp4 (5:10)
04.02 Change Multiple Worksheets (7:05)
04.03 Add And Count Worksheets (6:01)
04.04 Get Path Of A Workbook (5:14)
04.05 Open And Close Workbooks (8:41)
04.06 Loop Through Worksheets And Workbooks (8:20)
04.07 Build A Sales Calculator (11:54)
04.08 Change Charts (10:30)
04 Source Files
05 Work with the Range Object
05.00 Topics Overview (1:22)
05.01 Program A Range Of A Spreadsheet (6:55)
05.02 Use Cells Instead Of A Range (6:04)
05.03 Use A Range Variable (6:04)
05.04 Select A Range (4:52)
05.05 Access A Row (4:35)
05.06 Copy And Paste A Range (8:45)
05.07 Clear A Range (3:59)
05.08 Count A Range (4:21)
05 Source Files
06 Work with Range Properties
06.00 Topics Overview (1:03)
06.01 Find The Current Region Of A Cell (7:23)
06.02 Dynamic Range Program (7:11)
06.03 Resize A Range (2:30)
06.04 Select Entire Rows And Columns (6:33)
06.05 Offset Property (3:32)
06.06 End Property (5:06)
06 Source Files
07 More Range Projects
07.00 Topics Overview (1:21)
07.01 Union And Intersect Of Ranges (4:24)
07.02 Detect Content (5:38)
07.03 Build A Range Program (5:47)
07.04 Change Text Color (4:30)
07.05 Bold A Range (2:39)
07.06 Change Cell Color (5:04)
07.07 Work With Areas (4:55)
07.08 Find Differences In Ranges (8:17)
07 Source Files
08 Variables
08.00 Topics Overview (1:38)
08.01 Integer Data Type (2:58)
08.02 String Data Type (2:20)
08.03 Double Data Type (2:54)
08.04 Boolean Data Type (4:05)
08.05 Retain Variable Value (2:54)
08 Source Files
09 Work with Conditionals
09.00 Topics Overview (1:26)
09.01 If Then Statement (4:38)
09.02 Else Statement (4:55)
09 Source Files
10 Work with AND, OR and NOT
10.00 Topics Overview (1:21)
10.01 Greeting Program - Logical Operator And (4:00)
10.02 Logical Operator Or (5:37)
10.03 Logical Operator Not (3:15)
10 Source Files
11 Build Conditionals Projects
11.00 Topics Overview (1:58)
11.01 Select Case (5:42)
11.02 Build A Commission Calculator Project (6:11)
11.03 Find Remainder With Mod (3:11)
11.04 Check Number Program (6:38)
11.05 K Smallest Value Program (6:54)
11.06 Group By Font Style (6:45)
11.07 Remove Empty Cells (5:26)
11 Source Files
Introduction to Loops
00 Topics Overview (0:57)
01 Single Loop (5:59)
02 Double Loop (5:14)
03 Triple Loop (6:24)
04 Do While Loop (5:34)
05 Build A Commission Table (5:33)
Source Files
Loop Projects
00 Topics Overview (1:40)
01 Loop Through Defined Range (3:37)
02 Loop Through Entire Column (3:29)
03 Do Until Loop (3:22)
04 Use Step To Increment (4:23)
05 Build A Pattern Project (4:50)
06 How To Sort (5:32)
07 Sort By Related Data (8:15)
08 Delete Duplicate Values (6:10)
Source Files
String Manipulation
00 Topics Overview (1:28)
01 Join Strings (3:13)
02 Extract Substrings From Left Or Right (3:07)
03 Extract Substring At Middle (4:12)
04 Get Length Of A String (2:40)
05 Get Substring Position (3:16)
06 How To Split Strings (4:56)
07 Reverse Characters (4:10)
08 Change String Casing (3:28)
09 Count Words In A Range (8:17)
Source Files
Build Custom Functions
00 Topics Overview (1:19)
01 Make And Use Your Own Function (6:33)
02 Pass Arguments To A Function (7:43)
03 Custom Calculator Function (6:23)
Source Files
Build Arrays
00 Topics Overview (1:18)
01 One Dimensional Array (5:46)
02 Two Dimensional Array (6:26)
03 Change Array Size (4:54)
04 Build An Array (5:09)
05 Populate Row With Array (3:21)
06 Array Length (6:47)
07 Split String Into An Array (4:28)
08 Join Array Into A String (3:49)
Source Files
Work with Dates
00 Topics Overview (1:12)
01 Delay A Procedure (4:12)
02 Schedule A Procedure (4:18)
03 Count Years (5:20)
04 Count Days Between Dates (2:42)
05 Count Weekdays Between Dates (4:51)
06 Sort Dates (6:27)
Source Files
VBA Projects
00 Topics Overview (0:52)
01 Build A Table (4:47)
02 Build A Table Of Contents (11:47)
03 Build A Table Of Contents 2 (4:42)
04 Combine Worksheets (17:42)
05 Combine Worksheets By Column (15:49)
Source Files
Programming Charts
00 Topics Overview (1:20)
01 Program A Chart (6:12)
02 Program An Embedded Chart (4:59)
03 Delete Charts Programatically (2:19)
Source Files
LEVEL 4 🗣️🤝 Excel and ChatGPT Integration
01 01 What Is Chatgpt (7:50)
00-01 Introduction Of The Instructor (2:25)
01 02 Intro To Prompt Engineering-Prompt Types (8:28)
01 03 Intro To Prompt Engineering-Effective Prompts (8:41)
01B 01 Project Preview (2:04)
01B 02A Simplify Complex Information (8:38)
01B 02B Simplify Complex Information-Other Strategies (8:41)
02 03 Proofread-Email And Business Proposals (8:39)
02.03 Proofread-More Use Cases (8:24)
02.04 Re-Organize Data-Benefits And First Sample Use Case (6:22)
02.04 Re-Organize Data-Potential Use Cases Case (10:44)
02.05 Work With Spreadsheets-Automating Data Entry (7:46)
02.05 Work With Spreadsheets-Formulas And Other Use Cases (7:31)
03 01 Project Preview (1:23)
03.02 Create Content (4:03)
03.03 Social Media (4:26)
03.04 Write Ad Copy (8:17)
03.05 Write Email Marketing Campaigns (4:55)
03.06 Write An Outreach Message (5:08)
03.07 Copyrighting (4:29)
03.08 Seo (5:09)
03.09 Video Scripts (8:49)
03.10 Generate Text In Your Writing Style (3:25)
04 01 Project Preview (1:51)
04.02 Research-Chatgpt Usecase And Benefits (7:05)
04.02 Research-More Examples And Explanation (7:49)
04.03 Write An Article-Add Role To Chatgpt (7:17)
04.03 Write An Article-Generate High Quality Content (8:02)
04.04 Check Plagiarism (10:56)
04.05 Prepare For Job Opportunities-Cv And Cover Letter (8:28)
04.05 Prepare For Job Opportunities-Interview Questions, Connection And Task Generator (8:36)
05 01 Project Preview (2:33)
05.02 Generate Code-Javascript And Python Code Snippets (9:26)
05.02 Generate Code-Stylesheet, Html, C++ And Conversion (9:20)
05.03 Build Algorithms-Algorithm To Pseudocode (4:03)
05.03 Build Algorithms-Realworld Use Cases (8:11)
05.04 Debug-Python Use Case (6:51)
05.04 Debug-React, Api, Javascript, Html And Css (6:56)
05.05 Write Code Documentation (9:51)
05.06 Use Chatgpt As A Linux Terminal (8:32)
05.07 Use Chatgpt As A Unix Terminal (9:08)
05.08 Use Chatgpt As A Microsoft Dos Terminal (5:28)
05.09 Use Chatgpt To Suggest Uxui Designs (8:10)
05.10 Use Chatgpt To Suggest Cybersecurity Solutions (10:05)
Source Files
Introduction to JavaScript
01 Introduction To The Course (1:09)
Source file
02 Introduction Of The Instructor (0:36)
03 Why Should You Learn Javascript (0:51)
04 Quick Win (0:58)
05 Course Requirements (0:42)
02. Variables and Data Types
01 What Will We Learn In This Section (0:43)
Source Files
02 Variables (10:21)
03 Data Types (5:39)
04 Variable Mutation (6:53)
05 Type Coercion (6:52)
06 Coding Challenge (1:36)
07 Coding Challenge Solution (2:42)
08 Section Summary (0:50)
03. Operators
Source Files
01 What Will We Learn In This Section (0:35)
02 Basic Operators (15:34)
03 Operator Precedence (5:44)
04 Coding Challenge (2:14)
05 Coding Challenge Solution (5:52)
06 Section Summary (0:56)
04. Conditional Statements
01 What Will We Learn In This Section (0:35)
Source Files
02 If Else Statements (11:46)
03 Boolean Logic (7:59)
04 Switch Statements (10:53)
05 Truthy And Falsie Values (6:03)
06 Equality Operators (4:55)
07 Coding Challenge (2:25)
08 Coding Challenge Solution (4:54)
09 Section Summary (1:15)
05. Functions and Arrays
01 What Will We Learn In This Section (0:37)
Source Files
02 Functions (9:47)
03 Function Statements And Expressions (7:39)
04 Arrays (10:08)
05 Coding Challenge (3:52)
06 Section Summary (1:29)
06. Objects
Source Files
01 What Will We Learn In This Section (0:49)
02 Objects And Properties (9:50)
03 Objects And Methods (12:26)
04 Objects Vs Primitives (16:19)
05 Coding Challenge (0:53)
06 Coding Challenge Solution (5:16)
07 Section Summary (0:44)
07. Loops
Source Files
01 What Will We Learn In This Section (0:38)
02 Loops (15:16)
03 Iteration (12:38)
04 Coding Challenge (1:05)
05 Coding Challenge Solution (6:33)
06 Section Summary (0:50)
08. JavaScript Execution
01 What Will We Learn In This Section (0:57)
Source Files
02 Javasript Parsers And Engines (5:17)
03 Execution Contexts And Execution Stack (2:27)
04 Creation And Execution Phases (6:33)
05 Hoisting (2:14)
06 Scoping (4:53)
07 Scope Chain (3:21)
08 This Keyword (4:15)
09 Coding Challenge (0:47)
10 Coding Challenge Solution (3:22)
09. Build A JavaScript Project
01 What Will We Learn In This Section (0:38)
Source Files
02 Project Setup (9:55)
03 Events And Event Handling (17:10)
04 Make Updates (10:40)
05 State Variables (1:43)
06 Coding Challenge (0:41)
07 Coding Challenge Solution (2:37)
08 Section Summary (0:49)
10. Course Summary
Source Files
Course Summary (3:19)
ChatGPT 4 Prompt Engineering for Finance and Stock Market Investing
02 01 Project Preview (2:03)
01.01 Course Requirement (3:20)
02 02A Analyze Financial Statements Of Stock (9:00)
02 02B Financial Ratio And Trend Analysis (4:25)
02 03 Balance Sheet, Income Statement And Cash Flow Statement (9:00)
02 04 Loopholes And Weaknesses In Stock Financials (8:39)
02 05 Analyze Historical Stock Performance (11:16)
02 06 Predict Stock Performance (5:08)
02 07 Market Share (5:31)
02 08 Industry Analysis (7:48)
02 09 Management Team Analysis (8:25)
02 10 Analyze Stock Risks (6:56)
02 11 Valuation (8:11)
02 12 Explain Business Model Of A Company (6:24)
02 13 Perform A Swot Analysis (8:16)
02 14 Summarize A Company’S Earnings Report Calls (6:55)
02 15 Evaluate A Company’S Esg Credentials (4:39)
03 01 Project Preview (0:48)
03 02A Invest Short Term (6:22)
03 02B Implementing Your Short-Term Investment Strategy (8:06)
03 03A Invest Long Term (5:58)
03 03B Analyzing The Results (7:27)
03 04A Using Chatgpt To Assess Your Risk Tolerance (7:32)
03 04B Customized Investment Recommendations Based On Individual Financial Goals And Risk Tolerance (5:26)
03 04C Implementing Your Customized Investment Plan (8:47)
04 01 Project Preview (1:25)
04.02A Recent Past Stock Market State (7:44)
04.02B Analyzing Past Trends And Economic Events (9:24)
04.03A Present Stock Market State (6:29)
04.04A Future Stock Market State (8:12)
04.04B Insights On Macroeconomic Factors (7:09)
05 01 Project Preview (2:22)
05.02 Analyze Credit Scores (7:56)
05.03 Assess Loan Applicant Risk (7:35)
06 01 Project Preview (1:12)
06.02A Pick Stocks With Company Evaluation (6:00)
06.03A Build A Trading Strategy (8:54)
06.03B Test Trading Hypthothesis (8:29)
07 01 Project Preview (1:03)
07.02 Chatgpt And Sentiment Analysis (8:52)
07.03 Analyzing Sentiments On Social Media Posts- (8:45)
08 01 Project Preview (1:03)
08.02A Fraud Detection With Chatgpt (7:37)
08.02B Detecting Exploitation Prone Weaknesses (8:01)
08.03A Red Flags And Anomaly Detection (6:07)
08.03B Anomaly Detection Techniques (8:01)
Source Files
ChatGPT 4 for Marketing Professionals
Source file
00 01 Introduction Of The Instructor (1:53)
01.01 Setting Up Your Chatgpt Account - A Step-By-Step Guide (6:04)
01.02 Tips For Getting The Best Responses From Chatgpt (9:55)
02 01 Building A Marketing Campaign Content Calendar With Chatgpt (10:34)
03 01 The Importance Of Identifying Your Target Audience (3:08)
03.02 Using Chatgpt For Target Audience Research And Assessment (11:54)
04 01 Project Preview (1:21)
04.02 Exploring Social Media Marketing And Automation (5:59)
04.03 Generating Social Media Posts (10:38)
04.04 Social Media Automation Tool - Socialbee - -Bonus- (6:40)
04.05 Automating Social Media Post Scheduling - -Bonus- (8:26)
04.06 Automating Social Media Reposting - -Bonus- (8:28)
04.07 Configuring Your Social Media Automation Timetable – -Bonus- (4:00)
05 01 Project Preview (1:11)
05.02 Generate Optimized Keywords And Blog Headlines (7:39)
05.03 Building An Seo-Enhanced Blog Post Quickly (10:07)
06 01 Introduction To Email Marketing And Its Significance (3:37)
06.02 Building Effective Email Sequences (7:27)
07 01 Crafting Sales Page Copy (8:05)
08 01 Project Preview (1:07)
08.02 Producing Facebook Ads (10:00)
08.03 Generating Google Ads (9:44)
08.04 Generate Ads For Instagram And Twitter (7:36)
09 01 Project Preview (1:09)
09.02 Generating Unlimited Video Concepts (10:33)
09.03 Crafting A Full Youtube Video Script (10:00)
09.04 Youtube Seo Strategies (8:54)
10 01 Project Preview (1:26)
10.02 Guides To Building Effective Marketing Funnels (4:01)
10.03 Defining Your Buyer Persona (9:38)
10.04 Generating A Lead Magnet (8:57)
10.05 Building Landing Page And Social Media Copy (9:02)
10.06 Composing A Comprehensive Email Sequence For Your Funnel (4:49)
11 01 Review Analysis And Optimization Of Products And Services (7:24)
12 01 Project Preview (1:57)
12.02 Homepage, About Us, And Contact Us Page Copy (10:14)
12.03 Generate Meta Title And Descriptions (4:58)
12.04 Website Development With Chatgpt Crash Course (25:32)
13 01 Project Preview (1:10)
13.02 Creating Product And Business Names (7:52)
13.03 Developing Professional Taglines And Slogans For Your Brand (7:32)
13.04 Writing Product Descriptions For Your Online Store (4:46)
13.05 Building Faq’S For Services Or Products (4:54)
14 01 Conclusion (2:08)
Bonus - Tips And Tricks (7:43)
Advanced Business and Excel in ChatGPT
01.01 Course Requirement (2:31)
02.01 Project Preview (1:36)
02.02A Set Up Excel Spreadsheet With GPT Add-In (8:37)
02.02B Excel With ChatGPT (4:51)
02.03 Write Excel Formulas With ChatGPT (9:39)
02.04 Use ChatGPT Formulas In Excel (16:18)
03.01 Project Preview (1:27)
03.02A Set Up Dashboard (7:51)
03.02B Set Up Data (7:11)
03.03A Use ChatGPT And Excel To Build An Investment Dashboard (11:37)
03.03B Generate More Formulas For Excel (11:34)
03.03C Placing Data On Dashboard (10:30)
04.01 Project Preview (2:10)
04.02A Project Setup - Product Worksheet (11:59)
04.02B Setup Sales And Summary Sheet (9:22)
04.03A Build Advanced Chatgpt Excel Project (13:00)
04.03B Automating Product Name And Price Data (13:11)
04.03C Completing Sales Sheet Automation With Chatgpt (9:32)
04.03D Building Sales Overview Dashboard (8:37)
04.03E Refining The Pos System (11:14)
05 01 Project Preview (2:18)
05.02 Meeting Agendas And Minutes (10:25)
05.03 Write A Business Proposal (11:18)
05.04 Build A Business Report (11:12)
05.05 Build A Business Plan (10:35)
05.06 Build A Business Performance Appraisal (10:39)
05.07 Build A Business Presentation (12:40)
05.08 Summarize Business Documents (11:44)
05.09 Write Job Descriptions (8:33)
05.10 Build White Papers (9:38)
05.11 Build Employee Handbooks (8:44)
05.12 Build Business Manuals (9:24)
06.02 Set Up Project (1:16)
06.03A Advanced Chatgpt 4 Business Project (10:10)
06.03B Chatgpt And Social Bee Side By Side (10:16)
06.03C Finishing Touches (12:26)
Source File
ChatGPT for C-Level Management
01 01 Course Requirements (1:48)
01.02 What Is ChatGPT And Its Role With C-Level Management (1:35)
01.03 Overview Of Limitations And Capabilities (2:30)
02 01 Project Preview (1:43)
02.02 Drafting And Editing Business Content (13:36)
02.03 Branstorming Content Ideas (12:08)
02.04 Text Translation (13:39)
03.01 Project Preview (1:20)
03.02 Code Writing And Debugging (14:25)
03.03 Data Analysis And Summarization From Lower-Level Management (12:17)
04.01 Project Preview (1:49)
04.02 Generating Work Schedules (17:13)
04.03 Preparing For Interviews (17:34)
04.04 Task Delegation With Chatgpt (17:13)
05.01 Project Preview (1:14)
05.02 Writing Clear And Specific Prompts (6:47)
05.03A Privacy Considerations (11:25)
05.03B Things To Look At When Working With Chatgpt (9:50)
05.04 How To Provide Feedback For Continuous Learning (8:54)
Conclusion (2:58)
Tips And Tricks (10:11)
Source files
ChatGPT for Sales
01 01 Course Requirements (1:38)
01.02 Understanding Chatgpt (2:34)
01.03 The Role Of AI In Sales And Lead Generation (1:53)
01.04. Overview Of How Chatgpt Can Improve Outreach Strategy (1:34)
02 01 Project Preview (1:11)
02.02 How To Make Specific Asks (16:07)
02.03 Defining Terms For Chatgpt (3:15)
02.04 Understanding And Setting The Right Tone For Your Messages (13:05)
02.05 The Limitations Of AI In Sales And Lead Generation (12:45)
02.06 How To Utilize Chatgpt Effectively While Being Aware Of Its Limitations (16:09)
02.07 The Importance Of Checking And Editing AI Output (6:15)
03 01 Project Preview (1:18)
03.02 Defining Your Audience For Effective Outreach (19:40)
03.03 Using ChatGPT To Discover Audience Pain Points And How Your Product Solves Them (11:47)
03.04 Identifying Common Objections And Questions With Chatgpt (18:56)
03.05 Generating Cold Call Scripts, Elevator Pitches, And Battle Cards For Discovery Calls (15:16)
04 01 Project Preview (1:31)
04.02 Using Chatgpt To Generate Content Ideas For Nurturing Leads Through The Sales Funnel (19:10)
04.03 Sales Flow, Linked And Chatgpt (17:26)
05 01 Project Preview (0:59)
05.02 Understanding The Importance Of Linkedin For B2b Sales3 (3:04)
05.03A How To Use Chatgpt To Enhance Your Linkedin Sales Strategy (6:56)
05.03B ChatGPT And Linkedin Usecases (13:17)
05.03C Handling Lead Response With Chatgpt (6:48)
05.04 Best Practices For Using Chatgpt With Linkedin Message Templates For Higher Conversions- (8:36)
06 01 Project Preview (1:33)
06.02A Using Roleplay To Anticipate Pain Points And Objections (5:13)
06.02B Conversational Role Play (15:14)
06.03A Advance Techniques For Utilizing ChatGPT In Sales (9:55)
06.03B Advance Tips For Brainstorming And Analyzing Pain Points (10:25)
06.03C Secret Prompts For Better Response (18:16)
07 01 Privacy Considerations (19:27)
07.02 Feedbacks For Continuous Learning (5:21)
Source files
ChatGPT for Leadership
01 01 Preview Of The Course And Learning Objectives (1:57)
01.02 Course Requirements (2:10)
01.03 Role Of AI In Leadership (1:24)
01.04 How Chatgpt Can Aid Business Leaders (1:46)
02 01 Project Preview (0:56)
02.02A Examples Of Effective Chatgpt Prompts For Leadership (10:09)
02.02B Plugin System And More Effective Prompts (12:04)
02.03 Analyzing The Repsonse From Chatgpt (12:46)
02.04 Discussion And Analysis Of Chatgpt-s Generated Content (3:27)
03 01 Project Preview (1:36)
03 02 Understanding The Concept Of A Thought Partner (9:35)
03 03 How To Use Chatgpt As Thought Partner (15:11)
03 04 Providing Quick And Accurate Answers To Employee Queries (12:20)
03 05 Assisting In The Onboarding Process (17:20)
03 06 Improving Communication And Collaboration With The Help Of Chatgpt (14:51)
03 07A Providing Personalized Support To Team Members (9:49)
03.07B Tailored And Personalized Team Support (14:58)
03.08 Using Chatgpt For Training And Development (9:05)
03.09A Integrating Chatgpt Into Your Workflow (11:46)
03.09B ChatGPT As CEO (8:21)
04 01 Project Preview (2:15)
04.02 Enhancing Customer And Employee Engagement (16:28)
04.03 Tailoring Messages For Diffferent Audiences (8:50)
04.04 Using Chatgpt For Tricky Text Composition And Concept Explanation (9:13)
05 01 Project Preview (1:26)
05.02 Language Translation With Chatgpt For Global Business (17:32)
05.03 Using Chatgpt To Understand And Navigate Cultural Differences (7:07)
05.04 Successful Stories With Chatgpt (3:39)
06 01 Project Preview (1:26)
06.02A The Role Of AI In Data Analysis And Decision Making (13:17)
06.02B Sample Use Cases For Decision Making (13:19)
06.03 Utilizing Chatgpt For Strategic Planning And Forecasting (16:26)
Conclusion And Tips (20:04)
Source files
The Complete ChatGPT Automation Masterclass for Coaches and Trainers
01.01 Course Requirements
02.01 Getting Started (6:16)
03.01 Project Overview (2:02)
03.02A Utilizing Chatgpt In Training (9:52)
03.02B Automating Materials For Training Processes (9:42)
03.02C Use Case On Other Fields (10:02)
03.02D Chatgpt Web Browsing Feature (8:30)
03.02E Plugin System Overview (11:32)
04.01 Conclusion (1:24)
Source Files
Sales Analytics and Modeling in Excel with ChatGPT
1.1 Course Requirement (1:34)
02 01 Project Preview (0:57)
02.02. Sales Key Perfomance Indicators (KPIs) (10:16)
02.03.Measuring Salesperson Performance Using KPIs (5:48)
02.04.Marketing And Financial KPIs (6:49)
02.05.Customer-Related KPIs (10:20)
03 01 Project Preview (0:38)
03 02 Case Study Involving KPIs (3:09)
03.03. Joining Data Tables In Excel (7:28)
03.04.Cleaning Data Using Filters In Excel (5:19)
03.05.Determining Lead Conversion Time (5:19)
04 01 Project Preview (1:19)
04.02. Aggregating data by regions, categories, and time dimension (6:24)
04.03.Evaluating Salesperson Performance (13:59)
05 01 Project Preview (1:18)
05.02.Creating Charts To Visualize Sales Data (8:08)
05.03.Charting Region-Wise Percentage Contribution (6:22)
05.04.Charting Category-Wise Average Order Value (5:47)
05.05.Analyzing Lead Generation Trends (7:54)
05.06.Analyzing Salesperson Performance (6:26)
05.07.Building A Sales Dashboard (6:22)
05.08. Additional Charts For Sales Modeling (8:33)
06 01 Project Preview (1:33)
06.02.Building The Whale Model (6:47)
06.03.Lead Segmentation Using Decision Trees (6:53)
06.04.Excel Preparation For Analysis (6:52)
06.05.Case Study On Lead Segmentation (5:05)
06.06.Building A Model In Excel (9:38)
06.07.Interpreting Results From Tree Nodes (5:25)
06.08.Interpreting Results Based On Classification Criteria (5:23)
06.09.Drawing Inferences From Model Results (5:30)
06.10.Making Predictions Using The Trained Model (3:19)
06.11.Advanced Customization Options For Models (4:37)
07 01 Project Preview (1:05)
07.02.Market Basket Analysis For Cross-Selling Opportunities (11:01)
07.03.Predicting Values Using The Trained Model (6:27)
08 01 Project Preview (3:11)
08.02.Modeling Trends And Seasonality (10:03)
08.03.Additive And Multiplicative Time Series Models (9:30)
08.04.Linear Regression Model For Sales Forecasting (7:43)
08.05.Preprocessing Data For Regression (12:14)
08.06.Building A Linear Regression Model (8:27)
08.07.Predicting Values Using The Trained Model (8:26)
08.08.Using Xlstat For Forecasting (7:56)
09 01 Project Preview (1:52)
09.02.Building a Logistic regression model for churn prediction (12:17)
09.03.Predicting Churn Probability Using The Trained Model (11:05)
09.04.Evaluating Model Accuracy Using A Confusion Matrix (12:28)
Source Files
Introduction to Python
00. Introduction (4:42)
01.01 What Is Google Colab (4:24)
01.02 What If I Get Errors (2:40)
01.03 How Do I Terminate A Session (2:40)
02. Variables (19:17)
03. Type Conversion Examples (10:04)
04. Operators (7:04)
05. Operators Examples (21:52)
06. Collections (8:23)
07. Lists (11:38)
08. Multidimensional List Examples (8:05)
09. Tuples Examples (8:34)
10. Dictionaries Examples (14:24)
11. Ranges Examples (8:30)
12. Conditionals (6:41)
13. If Statement Examples (10:16)
14. If Statement Variants Examples (11:18)
15. Loops (7:00)
16. While Loops Examples (11:30)
17. For Loops Examples (11:18)
18. Functions (7:47)
19. Functions Examples (9:16)
20. Parameters And Return Values Examples (13:46)
21. Classes And Objects (11:13)
22. Classes Example (13:11)
23. Objects Examples (9:54)
24. Inheritance Examples (17:26)
25. Static Members Example (11:03)
26. Summary And Outro (4:06)
ChatGPT Prompts for Python Coders
Requirements
1 Introduction & Role of prompts in ChatGPT conversations (8:14)
2. Benefits of clear prompts (4:23)
3. Examples of good and bad prompts (11:18)
4. The 4-step approach to write the best prompts part 1 (6:57)
5. The 4-step approach to write the best prompts part 2 (5:37)
6. Example Python Prompts (14:40)
7. Unit Testing any Python App (20:28)
Source Code
Automate Power BI DAX and M with ChatGPT
01 Generate Employee Dataset With Chatgpt (4:50)
02 Copy Data Into Power BI And Generate A Query (10:34)
03 Calculate Employee Tenure With Power Query (10:39)
04 Filter Out Terminated Employees With Power Query (11:31)
Source
Generate queries to analyze employee performance
01 Filter By Performance Rating With Power Query (7:12)
02 Categorize Performance With Power Query (5:49)
03 Compare Employee Performance With Location And Education (14:57)
04 Find Top Performing Employees With Power Query (10:26)
05 Calculate Performance For Age Groups (5:35)
Source
Generate DAX queries with ChatGPT for Power BI
01 Generate simple DAX queries with ChatGPT for Power BI (8:02)
02 Count rows by category with DAX (11:27)
Source
Build DAX queries to generate tables with ChatGPT
01 Build Dax Queries To Generate Tables With ChatGPT (4:49)
02 Group Employees With Dax Queries (3:30)
Source
Build visualizations in Power BI with ChatGPT
01 Build Visualizations In Power BI With ChatGPT (6:58)
Source files
Anomaly Detection in Credit Card Transactions with Python
00 Project Preview - Python Data Visualization In Power BI With Chatgpt (3:54)
01 Generate Credit Card Data With Chatgpt (7:07)
02 Detect Anomalies With Z-Score In Python (18:39)
Source
Visualize data with Python in Power BI
01 Visualize Transaction Amount For Each Merchant (6:55)
02 Visualize Trend Of Transaction Amounts Over Time (18:25)
03 Show Pie Distribution Of Transaction Amounts By Category (8:48)
04 Show Histogram Distribution Of Transaction Amounts (2:11)
Source
Visualize data across categories with ChatGPT
01 Compare Amounts Across Categories With Box Plot (4:23)
02 Show Amount For Each Period By Category (7:14)
03 Visualize Transaction Amounts For Each Merchant (14:00)
04 Build A Word Cloud For Product Names (5:07)
Source
Generate machine learning models with ChatGPT
00 Project Preview - Python Machine Learning With Chatgpt (2:03)
01 What Kinds Of Machine Learning Can I Do On This Data (2:16)
02 Build A Linear Regression Model For Credit Card Dataset (8:35)
02B Visualize Linear Regression Training With Gif (10:43)
03 Logistic Regression With Confusion Matrix And Scatter Plot (14:26)
Source
Build tree machine learning models with ChatGPT
01 Build Decision Tree Model For Credit Card Dataset (8:03)
02 Build A Random Forest Model With Bar Plot (4:17)
Source
Build advanced models with ChatGPT and Python
01 Build SVM Scatter Plot With ChatGPT (21:28)
02 Build Gradient Boosting With A Bar Chart (14:22)
Source
Data Science with Python and NumPy - Introduction to Tensorflow
00. Course Intro (6:10)
01. Intro To Tensorflow (5:33)
02. Installing Tensorflow (3:52)
03. Intro To Linear Regression (9:26)
04. Linear Regression Model - Creating Dataset (5:49)
05. Linear Regression Model - Building The Model (7:22)
06. Linear Regression Model - Creating A Loss Function (5:57)
07. Linear Regression Model - Training The Model (12:43)
08. Linear Regression Model - Testing The Model (5:22)
09. Summary And Outro (2:55)
Intro to Tensorflow - Source Files
Machine Learning theory
00. Course Intro (6:05)
01. Quick Intro To Machine Learning (9:01)
02. Deep Dive Into Machine Learning (6:01)
03. Problems Solved With Machine Learning Part 1 (13:26)
04. Problems Solved With Machine Learning Part 2 (16:25)
05. Types Of Machine Learning (10:15)
06. How Machine Learning Works (11:40)
07. Common Machine Learning Structures (13:51)
08. Steps To Build A Machine Learning Program (16:34)
09. Summary And Outro (2:49)
Intro to Machine Learning Slides
Numpy
00. Course Intro (5:11)
01. Intro To Numpy (6:21)
02. Installing Numpy (3:59)
03. Creating Numpy Arrays (16:55)
04. Creating Numpy Matrices (11:57)
05. Getting And Setting Numpy Elements (16:59)
06. Arithmetic Operations On Numpy Arrays (11:56)
07. Numpy Functions Part 1 (19:13)
08. Numpy Functions Part 2 (12:36)
09. Summary And Outro (3:01)
Source Files
Review Sentiment Analysis
00. Course Intro (6:19)
01. How Machines Interpret Text (15:23)
02. Building the Model Part 1 - Examining Dataset (12:27)
03. Building the Model Part 2 - Formatting Dataset (15:14)
04. Building the Model Part 3 - Building the Model (10:30)
05. Building the Model Part 4 - Training the Model (5:42)
06. Building the Model Part 5 - Testing the Model.mp4 (9:26)
07. Course Summary and Outro (3:29)
Source Files
Learn to Graph Data with Python and Matplotlib
00. Course Intro (5:30)
01. Intro To Pyplot (5:11)
02. Installing Matplotlib (5:52)
03. Basic Line Plot (7:53)
04. Customizing Graphs (10:47)
05. Plotting Multiple Datasets (8:10)
06. Bar Chart (6:26)
07. Pie Chart (9:13)
08. Histogram (10:14)
09. 3D Plotting (6:28)
10. Course Outro (4:09)
Pyplot Code
Complete Beginners Data Analysis with Pandas and Python
00. Panda Course Introduction (5:43)
01. Intro To Pandas (7:55)
02. Installing Pandas (5:28)
03. Creating Pandas Series (20:34)
04. Date Ranges (11:29)
05. Getting Elements From Series (19:21)
06. Getting Properties Of Series (13:04)
07. Modifying Series (19:02)
08. Operations On Series (11:48)
09. Creating Pandas Dataframes (22:57)
10. Getting Elements From Dataframes (25:12)
11. Getting Properties From Dataframes (17:44)
12. Dataframe Modification (36:24)
13. Dataframe Operations (20:09)
14 Dataframe Comparisons And Iteration (15:35)
15. Reading Csvs (12:00)
16.Summary And Outro (4:14)
Source Files
Automate Excel Data Manipulation with Python and ChatGPT - 01 Handle missing data with Python and ChatGPT
01 Algorithms To Handle Missing Data (5:13)
02 Generate Excel Data With Missing Data In Python And ChatGPT (3:22)
03 Fill In Missing Excel Data With Python Imputation And ChatGPT (3:51)
04 Delete Missing Excel Data With Python And ChatGPT (5:03)
05 Fill In Missing Data With Knn Imputation (5:24)
Source
02 Categorical data manipulation with Python and ChatGPT
01 What Is Data Encoding (5:36)
02 Perform Excel Data Encoding With Python And ChatGPT (7:18)
03 Choose Data Encoding Technique (3:01)
Source
03 Statistics for data science with Python and ChatGPT
01 What Is Statistics For Data Science (3:31)
02 Levels Of Data Measurement (3:58)
03 Generate Different Types Of Data With ChatGPT (10:02)
Source
04 How to measure data
01 Measures Of Central Tendency In Data (5:00)
02 Measures Of Variability In Data (4:09)
03 What Is Skewness In Data Science (3:38)
04 Generate Skewed Datasets With ChatGPT (7:44)
05 What Are Covariance And Correlation Data Measurements (2:37)
06 Measure Covariance And Correlation Of Dataset With Chatgpt (6:50)
Source
05 Probability distribution functions in data science
01 What Are Probability Distribution Functions In Data Science (4:39)
02 Calculate Probability Distribution Functions Of A Dataset With ChatGPT (5:22)
Source
06 Normal Probability Distribution with Python and ChatGPT
01 What Is Normal Probability Distribution (4:14)
02 Calculate PDF Of Normal Distribution Dataset (5:35)
03 What Is The Central Limit Theorem (2:45)
Source
07 Binomial Probability Distribution with Python and ChatGPT
01 What Is Binomial Probability Distribution (2:52)
02 Calculate Pdf Of Binomial Distribution Dataset (10:50)
Source
08 Poisson Probability Distribution with Python and ChatGPT
01 What Is Poisson Probability Distribution (2:42)
02 Visualize Poisson Distribution With ChatGPT And Python (2:31)
Source Files
09 Uniform Probability Distribution with Python and ChatGPT
01 What Is Uniform Probability Distribution (2:36)
02 Visualize Uniform Distribution With ChatGPT And Python (3:55)
Source Files
10 Bernoulli Probability Distribution with Python and ChatGPT
01 What Is Bernoulli Probability Distribution (2:37)
02 Visualize Bernoulli Distribution With Chatgpt And Python (6:43)
Source Files
Master the API
00b-01 Openai API Models To Work With (2:53)
00b-02 How OpenAI API Works (2:09)
00b-03 Adjust OpenAI API Model Parameters (7:58)
01-01 Use OpenAI API To Answer Questions Like Chatgtp (10:19)
01-02 Correct Grammar With OpenAI API (3:30)
01-03 Summarize And Simplify Text With OpenAI API (4:03)
01-04 Translate Text With OpenAI API (3:04)
02-01 Generate Code With OpenAI API (7:11)
02-02 Explain Code With Openai Api (5:24)
02-03 Calculate Time Complexity With Openai Api (3:40)
02-04 Translate Programming Languages With OpenAI API (4:24)
02-05 Fix Bugs In Code With Openai Api (3:19)
03-01 Generate Sql Queries With Openai Py (5:15)
03-02 Build Structured Table Data From Long Form Text (4:29)
03-03 Classify Items Into Categories With Openai Api (4:50)
03-04 Generate Spreadsheets And Lists With Chatgpt Openai Api (5:46)
04-01 Convert Notes To Summary With Openai Api (5:40)
04-02 Add Emotional Sentiment To Text With Openai Models (9:40)
04-03 Generate Questions On A Topic With Gpt Turbo (9:26)
04-04 Generate Text Conversation With Chatgpt Api (5:19)
05-01 Classify Text Emotion Sentiment With Chatgpt Models (5:09)
05-02 Extract Keywords From Text With Chatgpt Api (4:31)
05-03 Convert Product Description To Ad With Chatgpt Python (3:57)
05-04 Generate Product Names With Chatgpt In Python (4:04)
05-05 Extract Information From Text With Chatgpt Api (2:57)
06-01 Build Html Parser With Python (4:31)
06-02 Scrape Hyperlinks From Url Webpage With Python (4:09)
06-03 Filter Out Urls Not Part Of Domain (7:03)
06-04 Save Web Content To Files With Python (10:07)
07-01 Convert Text To Csv With Python (6:36)
07-02 Remove Whitespace And Lines From Text With Python (4:58)
07-03 Tokenize Text With Python For Machine Learning Models (2:50)
07-04 Split Long Lines With Python (4:11)
07-05 Split Pandas Dataframe Into Sections With Python (7:19)
07-06 Embed Text For Machine Learning With Openai Api (8:05)
08-01 Embed Question With Python (5:48)
08-02 Answer Questions About Your Data With Customized Openai Model (10:36)
09-01 Load And Read Pdf In Python (3:40)
09-02 Build Vector Index From Pdf Text In Python (4:32)
09-03 Answer Questions About Pdf With Chatgpt Model In Python (5:10)
10-01 Generate Review Data With Chatgpt Api (8:14)
10-02 Format Python Text To Multidimensional Pandas Dataframe (11:50)
10-03 Change Column Data Type In Pandas Dataframe (2:40)
10-04 Embed Text Data With Openai Api (6:25)
Source files
ChatGPT 4 for Web Developers - Build an E-commerce Site with JavaScript
01. Short Demo - Introduction To The Course (2:25)
02. Project Setup (16:38)
03. Css With Chatgpt Part 1 (27:38)
04. Css With Chatgpt - Part Two (20:52)
05. Styling The Product-Info Page (24:47)
06. Links, Burger Menu And Filters (16:16)
07. Implementing The Shopping Cart - Part One (16:54)
08. Implementing The Shopping Cart Part Two (10:30)
09. Total Price And Shipping Calculations (24:13)
10. Checkout Page (18:43)
11. Styling The Site Pt1 (15:51)
12. Styling The Site Pt2 (17:25)
13. Legacy Pages (23:06)
14. Login Register Dashboard (25:55)
15. Local Storage For User Info (20:34)
Source Files
LEVEL 5 🎤💡 Pass the Excel & AI Coding Interview - Excel to Python Data Science Automation
00 Course Overview - Excel To Python (7:06)
00 Project Overview - Excel Automation With Python Data Modeling (0:55)
01 Read Excel File With Python (6:43)
02 Reshape Data For Data Modeling (5:29)
03 Build A Linear Regression Model With Python (5:01)
04 Visualize Machine Learning Predictor With Python (6:22)
Source Files
Use Excel File in Python
01 Use Excel File In Python (9:56)
02 Manipulate Excel File With Python (4:30)
03 Build Dictionaries With Python (3:51)
Source Files
Manipulate Excel Sheets with Python
01 Import Data File Into A Pandas Dataframe (6:22)
02 Excel Sheet Manipulation With Python (6:01)
03 Get Excel Sheet Information With Python (4:15)
Source Files
Build Excel Filters in Python
01 Build View Excel Functions In Python (5:58)
02 Build Filter Excel Functions In Python (3:31)
03 Build Filter Functions On Blockchain Dataset (11:04)
Source Files
Aggregate Excel Data with Python
01 Aggregate Excel Data With Python (11:21)
02 Build Excel Pivot Tables In Python (5:19)
Source Files
Automate Excel Files with Python OpenPyXL
01.00 Course Overview (2:20)
01.01 Run Openpyxl On The Web (1:45)
02.01 Make A Workbook (11:01)
02.02 Save A Workbook (3:51)
02.03 Read A Workbook (8:02)
02.04 Work With Rows And Columns (8:07)
02.05 Use A Formula (8:41)
02.06 Use Dates (7:18)
02.07 Merge And Unmerge Cells (7:11)
02.08 Fold A Range (6:17)
02.09 Make A New Sheet (3:17)
02.10 Copy Data To A Sheet (4:35)
02.11 Remove A Sheet (3:45)
03.01 Build A Table (15:50)
03.02 Style A Table (8:56)
03.01 Import Dataset (4:20)
03.02 Style A Cell (6:47)
03.03 Make A Named Style (6:57)
03.04 Copy A Style (4:59)
04.01 Make A Chart (11:04)
04.02 Build Line Charts (15:30)
04.03 Build A Pie Chart (14:09)
04.04 Build A Scatter Chart (11:22)
04.05 Build An Area Chart (8:22)
05.01 Project Setup (4:30)
05.02 Expand Columns To Fit Content (6:35)
05.03 Add Dates (7:34)
05.04 Add Days Of The Week (7:11)
06.01 Read Spreadsheet Data (7:11)
06.02 Store Spreadsheet Data (3:39)
06.03 Write To A Text File (5:22)
07.01 Set Up Update Information (3:44)
07.02 Update The Spreadsheet (5:41)
08.01 Build A Stock Chart (9:14)
08.02 Build A Doughnut Chart (9:22)
08.03 Build A Bubble Chart (8:53)
09.01 Import Web Driver (8:06)
09.02 Scrape A Web Page (6:07)
09.03 Parse Page Data (9:17)
09.04 Put Data Into Excel Sheet (6:22)
09.05 Clean Data (4:38)
Source Files
Web Automation with Selenium Python
00.00 What You-ll Learn (5:43)
00.01 Install Selenium (9:12)
00.02 Download Visual Studio Code (4:10)
01.01 Find Elements By Name (14:50)
01.02 Find Elements By Id (7:34)
01.03 Find Elements By Xpath (12:29)
01.04 Find Input Field By Xpath (13:44)
01.05 Find Elements By Css Selector (9:14)
01.06 Find Elements By Link Text (7:47)
01.07 Find Elements By Partial Link Text (8:05)
01.08 Find Elements By Classname (6:22)
01.09 Find Elements By Tagname (7:29)
02.01 Automate A Google Search (19:41)
02.02 Automate Navigating A Dropdown Menu (16:22)
02.03 Automate Changing Tabs (15:41)
02.04 Automate Alert Popups (13:26)
03.01 Explicit Waits (21:04)
03.02 Implicit Waits (8:45)
04.01 Automate Window Size (12:04)
04.02 Get Title And URL (4:12)
04.03 Automate Closing Vs Quitting Windows (4:06)
05.01 Mouse Hover (14:01)
05.02 Automate Mouse Click (7:40)
05.03 Right Click (6:26)
05.04 Automate Double Click (8:36)
05.05 Click, Hold And Release (7:17)
06.01 Web Scrape Images (13:29)
06.02 Automate Downloading Images (27:34)
Source Files
The Ultimate Amazon Honeycode Guide
01 Course Overview (4:00)
02 How To Sign Up (1:21)
03 Beta (0:46)
Build Your First App
01 Project Overview (5:49)
02 Set Up Data Tables (10:26)
03 Build Your First App (12:12)
04 Customize App And Add Navigation (7:54)
05 Add Automated Notifications (9:38)
Build an App Backwards with Data
01 Project Overview (2:27)
02 Format Data (22:15)
03 Build The App (23:48)
04 Style And Customize The App (20:32)
05 Automation And Edge Cases (10:38)
Content Tracker
01 Content Tracker Overview (4:49)
02 Content Tracker Database (13:29)
Build Apps with Objects
01 Data Cell (15:34)
02 Content Box (5:25)
03 Button (9:53)
04 Blank Block (4:04)
05 Blank List (13:24)
06 Column List (7:47)
07 Stacked List (8:22)
08 Form (7:35)
09 Input Field (6:57)
10 Picklist (8:13)
11 Number (6:13)
12 Percentage (5:06)
13 Currency (3:15)
14 Contact (4:37)
15 Date (4:25)
16 Segment (3:53)
17 Screen (4:39)
Simple Survey
01 Simple Survey Overview (4:45)
02 Simple Survey Database (5:50)
Inventory Management
01 Inventory Management Overview (7:06)
02 Inventory Management Database (12:57)
To Do List
01 To Do List Overview (4:34)
02 To Do List Database (11:12)
Introduction to Blockchain (Prerequisite)
00 Blockchain Introduction (8:32)
01 What Are Blockchains And Distributed Ledgers (3:48)
02 What Are Bitcoin And Ethereum (5:28)
03 Introduction To Crypto Trading (2:44)
Python SQL Ethereum Data Science with Google BigQuery
00 Course Overview - Ethereum Sql (7:07)
01 What Are Google Cloud Platform And Bigquery (6:01)
02 Build A Project On Google Cloud Platform (4:26)
Source Files
Simple BigQuery Python SQL queries
01 Find Entries In Big Query Public Dataset (10:16)
02 Filter Entries By State Column (9:11)
Source files
Simple BigQuery Ethereum queries
01 Query Tables In Crypto Ethereum Big Query Public Dataset (4:45)
02 Select Ethereum Traces By Date (9:05)
03 Get Total Ether Supply Each Day (3:40)
04 Select Transactions By Address And Timestamp (10:13)
Source files
Calculate transaction ratios
01 Get Zero Transaction Ratio For Blockchain (10:56)
02 Get Zero Transaction Ratio For Smart Contracts (8:41)
Source files
Introduction to Machine Learning
What Is Machine Learning (5:26)
What Is Inductive Learning (4:11)
How Does A Machine Learning Agent Learn (7:38)
Types Of Machine Learning Models (12:17)
01 What Is Supervised Learning (11:04)
02 What Is Unsupervised Learning (8:17)
03 Performance Of A Machine Learning Algorithm (4:14)
04 Handle Noise In Data (5:22)
05 Powerful Tools With Machine Learning Libraries- (12:11)
Beginner Data Science and Machine Learning Bootcamp
01 Project Preview (3:29)
02 Create A Dataset (5:17)
03 Vectorize Text (16:27)
04 Build A Word Cloud (7:08)
05 Reduce Data Dimensionality With Principal Component Analysis (6:08)
06 Perform Unsupervised Classification With K-Means Clusters (17:33)
Source Files
Machine Learning Fundamentals
00 Course Overview (13:46)
01 Probability And Information Theory Overview (5:15)
02 Combinatorics For Probability (8:44)
03 Law Of Large Numbers (10:38)
04 Calculate Center Of Distribution (7:40)
05 Uniform Distribution (5:25)
06 Gaussian Distribution (3:45)
07 Log-Normal Distribution (3:28)
08 Exponential Distribution (3:04)
09 Laplace Distribution (1:54)
10 Binomial Distribution (9:05)
11 Multinomial Distribution (3:59)
12 Poisson Distribution (4:21)
13 Calculate Error Of Machine Learning Model (8:44)
Source Files
Data Engineering and Machine Learning Masterclass
00b-00 Course Overview (3:26)
03-01 Load And Clean A Public Dataset (8:55)
03-01B What Is One-Hot Encoding (10:02)
03-02 Build X And Y Data With One Hot Encoding (4:57)
03-03 Logistic Regression With One Hot Encoding (2:20)
04-04 Scale And Encode Data With Scikit-Learn (3:47)
04-04 What Is Scaling Data (6:36)
04-05 Build, Train And Test A Machine Learning Model (4:37)
05-01 Compare Decision Tree And Linear Regression Models (6:26)
05-01 What Is The Kbins Discretizer (4:54)
05-02 Bin Data With Kbins Discretizer (3:42)
05-03 Compare Binned Regression Models (3:39)
05-04 Build A Linear Regression Model On Stacked Data (3:20)
05-05A What Is K Means Clustering (11:58)
06-01 Build Univariate Nonlinear Transformatio (1:55)
06-01 What Is Gaussian Probability Distribution- (2:31)
06-01B What Is Poisson Distribution (1:08)
06-02 Build X Y Data With Poisson Distribution In Numpy (3:34)
06-02 What Is Logarithmic Data Transformation (2:34)
06-03 Build A Ridge Regression Model (3:41)
Source Files
Image recognition with MNIST
00. Course Intro (6:57)
01. Intro to Image Recognition (6:40)
02. Intro to MNIST (4:42)
03. Building a CNN Part 1 - Obtaining Data (15:40)
04. Building a CNN Part 2 - Building the Model (10:14)
05. Building a CNN Part 3 - Adding Loss and Optimizer Functions (4:57)
06. Building a CNN Part 4 - Train and Test Functions (10:58)
07. Building a CNN Part 5 - Train and Test the Model (9:17)
08. MNIST Image Recognition with Keras Sequential Model (13:24)
09. Summary and Outro (2:55)
Source Files
Build Machine Learning Models
01-01 Course Overview (3:30)
01-02 Build Models On The Web (5:06)
02-01 What Are Search Algorithms (7:21)
02-02 Depth First Search (9:00)
02-02b Build A Depth First Search Algorithm (8:26)
02-03 What Is Breadth First Search (bfs) (5:08)
02-03b Build A Breadth First Search Algorithm (6:56)
02-04 Depth Limited Search (3:58)
02-05 Iterative Deepening Depth First Search (5:32)
02-06 What Is Uniform Cost Search (6:04)
02-06b Build A Uniform Cost Search Algorithm (8:07)
02-07 Bidirectional Search (4:44)
03-01 What Are Informed Search Algorithms (4:07)
03-02 What Is Greedy Best-first Search (8:16)
03-02b Build A Greedy Best First Search Algorithm (10:43)
03-03 What Is A Search (5:10)
04-01 How Does A Machine Learning Agent Learn (7:37)
04-02 What Is Inductive Learning (4:10)
04-03 Make Decisions With Decision Trees (10:50)
04-04 Performance Of A Machine Learning Algorithm (4:13)
04-05 Handle Noise In Data (5:20)
04-06 Statistical Learning (3:56)
05-01 What Is Logistic Regression (4:26)
05-03a How To Prepare Data (8:52)
05-03 Prepare Data For Logistic Regression (12:19)
05-04a How To Build A Logistic Regression Model (3:28)
05-04 Build A Logistic Regression Model (5:29)
05-04b What Is Optimization (12:10)
05-05a How To Optimize A Logistic Regression Model (12:45)
05-05 Optimize The Logistic Regression Model (12:44)
05-06 Train The Model (10:09)
05-07 Test The Model (2:33)
05-08 Visualize Results (5:38)
06.01 What Is Gradient Boosting (1:54)
06.02 Prepare Data For Gradient Boosted Classification (7:19)
06.03 Build Binary Classes (6:12)
06.04a How To Shape Data For Classification (2:58)
06.04b Shape Data For Classification (7:06)
06.05a How To Build A Boosted Trees Classifier (4:03)
06.05b Build A Boosted Trees Classifier (4:37)
07.01 Build Input Functions (3:55)
07.02 Build A Boosted Trees Regressor (3:02)
07.03 Train And Evaluate The Model (4:07)
08.01 What You'll Learn (8:47)
08.02 What Is Supervised Learning (14:41)
08.03 Build Models On The Web (5:06)
Source Files
Data Science with Stocks, Excel and Machine Learning
00.00 Course Overview (5:43)
01.00 What You-ll Learn (2:01)
01.01 Pull In Stock Data (8:21)
01.02 Pull In More Stock Information (5:08)
01.03 Calculate Equity And Returns (11:56)
01.04 Calculate Selling Strategy (9:25)
01.05 Calculate Total Returns (4:28)
02.01 Pull Historical Stock Data (2:31)
02.02 Predict Stocks With Moving Average (9:34)
02.03 Visualize Accuracy (3:48)
02.04 What Is Exponential Smoothing (4:15)
02.05 Predict Stocks With Exponential Smoothing (7:37)
02B.00 What You-ll Learn (1:46)
02B.01 Pull Historical Stock Data (5:49)
02B.02 What Is Linear Regression (4:45)
02B.03 Linear Regression On Stock Data In Excel (8:04)
02B.04 Check Accuracy Of Linear Regression (12:53)
03.00 What You-ll Learn (2:01)
03.01 Build Models On The Web (5:05)
03.02 What Libraries Will We Use (5:56)
03B.01 Scrape Data Via API (16:42)
03B.02 Define Variables (11:37)
03B.03 Split Dataset For Training And Testing (7:33)
03B.04 Build A Linear Regression Model (9:16)
03B.05 Predict Stock Prices (10:14)
03B.06 Calculate Model Accuracy (14:17)
03B.07 Predict To Buy Or To Sell (7:23)
04.00 Recurrent Neural Networks (6:23)
04.01 Import Stock Data (9:19)
04.02 What Is Shaping Data (5:18)
04.03 Shape Training And Testing Data (12:06)
04.04 What Is Scaling Data (6:35)
04.05 Scale Data For Training (11:24)
04.06 What Is Keras (3:24)
04.07 Build A Keras Model (14:04)
04.08 Scale And Shape Data For Testing (5:33)
04.09 Test The Model (5:15)
Source Files
Ace the Python Coding Interview
01 Introduction Python (6:17)
02 Fizzbuzz Python (5:57)
Source Code
Time Complexity
00 Types Of Time Complexity Python (21:51)
01 Types Of Better Time Complexity Python (14:51)
Source Code
02 String and Array Interview Questions
01 Reverse Words In A String Python (2:44)
02 Rotate Array Python (8:56)
03 Kth Smallest Element In An Array Python (11:53)
Source Code
03 Matrix Interview Questions
01 Spiral Matrix Python (13:26)
02 Number Of Islands Python (18:54)
Source Code
04 Linked List Interview Questions
01 Inorder Traversal Python (11:08)
02 Preorder Traversal Python (8:48)
03 Postorder Traversal Python (7:05)
04 Binary Tree Maximum Path Sum Python (8:43)
Source Code
05 Binary Tree Interview Questions
01 Inorder Traversal Python (11:08)
02 Preorder Traversal Python (8:48)
03 Postorder Traversal Python (7:05)
04 Binary Tree Maximum Path Sum Python (8:43)
Source Code
06 Graph Interview Questions
01 Find Strongly Connected Components Python (10:29)
Source Code
07 Sorting Interview Questions
01 Bubble Sort Algorithm Python (9:11)
02 Selection Sort Algorithm Python (5:56)
03 Insertion Sort Algorithm Python (4:29)
04 Quicksort Algorithm Python (4:29)
05 Merge Sort Algorithm Python (7:25)
06 Time Complexity Of Different Sorting Algorithms (2:55)
Source Code
08 Dynamic Programming Interview Questions
01 Coin Change Python (7:21)
02 Edit Distance Python (11:33)
03 Distinct Subsequences Python (6:59)
04 Maximum Sum Subarray Python (4:56)
Source Code
09 Bit Manipulation Interview Questions
01 Bitwise And Shift Operators (7:02)
02 Single Number Python (4:32)
03 Number Of 1 Bits Python (4:31)
04 Sum Of Two Integers Python (5:14)
05 Bitwise And Of A Range Python (5:36)
Source Code
10 Permutations and Combinations
01 Permutations Python (10:08)
02 Distinct Permutations Of A String Python (7:49)
03 Letter Combinations Of A Phone Number Python (11:54)
Source Code
11 Math Interview Questions
01 Reverse Integer Python (9:53)
02 Palindrome Number Python (9:49)
03 Excel Sheet Column Number Python (6:04)
Source Code
Machine Learning Interview Questions
00. Course Intro (5:09)
01-00. Intro (1:54)
01-01. What is Machine Learning (17:47)
01-02. Types Of Machine Learning (10:48)
01-03. Building A Machine Learning Model (17:02)
02-00. Intro (2:44)
02-01. How To Choose An Algorithm (16:42)
02-02. Common Machine Learning Algorithms Part 1 (15:58)
02-03. Common Machine Learning Algorithms Part 2 (22:52)
02-04. Common Machine Learning Algorithms Part 3 (13:03)
02-05. Comparison Interview Questions (16:20)
03-00. Intro (2:08)
03-01. Data Related Errors (16:55)
03-02. Model Related Errors (11:34)
03-03. Results Testing Techniques (11:18)
04-00. Intro (2:14)
04-01. Missing_Corrupted Data (5:08)
04-02. Selecting Important Variables (3:18)
04-03. Fixing Multicollinearity- (3:56)
04-04. Kernel Tick (3:21)
04-05. Slow Machine_Limited Memory (4:59)
04-06. Classification and Random Sampling (3:38)
04-07. Low Training Error with High Validation Error (4:40)
04-08. Cross Validation on Time Series Data (3:38)
04-09. Amazon Recommendation System (5:26)
05. Course Summary and Outro (3:12)
Source Files
04.02. Aggregating data by regions, categories, and time dimension
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