Learn Python Data Science and Machine Learning Classification
Machine learning is quickly becoming a required skill for every software developer.
Build Projects with Machine Learning, Text Classification, TensorFlowNumPy, PyPlot, Pandas, and More in Google Colab
Learn everything you need to become a data scientist.
Enroll now to learn everything you need to know to get up to speed, whether you're a developer or aspiring data scientist. This is the course for you.
Your complete Python course for image recognition, data analysis, data visualization and more.
Don't miss the biggest Python course of the year. This is a once in a lifetime chance to enroll in a massive course.
Absolutely no experience necessary. Start with a complete introduction to Python that is perfect for absolute beginners and can also be used a review.
Jump into using the most popular libraries and frameworks for working with Python. You'll learn everything you need to become a data scientist. This includes:
0. Python Crash Course for Beginners
Learn Python with project based examples. Get up and running even if you have no programming experience. Superboost your career by masterig the core Python fundamentals.
1. Data Science with NumPy
Build projects with NumPy, the #1 Python library for data science providing arrays and matrices.
2. Data Analysis with Pandas
Build projects with pandas, a software library written for the Python programming language for data manipulation and analysis.
2. Data Visualization with PyPlot
Build projects with pyplot, a MATLABlike plotting framework enabling you to create a figure, create a plotting area in a figure, plot lines in a plotting area, decorate the plot with labels and much more. Learn it all in this massive course.
3. Machine Learning Theory
Machine learning is in high demand and is quickly becoming a requirement on every software engineer's resume. Learn how to solve problems with machine learning before diving into practical examples.
4. Introduction to TensorFlow
Build projects with TensorFlow, the most popular platform enabling ML developers to build and deploy machine learning applications such as neural networks. Build your first linear regression model with TensorFlow. Learn how to build a dataset, model, train and test!
5. Build a Sentiment Analysis Model to Classify Reviews as Positive or Negative
All source code is included for each project.
If you buy one course this year, this is it. Sign up while spots are open.
Who this course is for:
 Anyone who needs to learn sentiment analysis and more
 Anyone who needs to learn Python
 Anyone who needs to know more about machine learning
 Anyone who needs to graph with Python
 Anyone with no Python experience
 Anyone who needs an efficient way to analyze data
 Anyone with little to no programming experience
 Anyone who wants to use efficient arrays
 Anyone with little to no knowledge of machine learning
What you'll learn
 Process text data
 Interpret sentiment in reviews
 Build a model to predict whether a review is positive or negative
 Implement logic
 Track data
 Customize graphs
 Implement responsiveness
 Build data structures
 Graph data with PyPlot
 Build 3D graphs with PyPlot
 Use common array functions
 Replace Python lists with NumPy arrays
 Build and use NumPy arrays
 Use Pandas series
 Use Pandas Date Ranges
 Read CSVs with Pandas
 Use Pandas DataFrames
 Get elements from a Series
 Get properties from a series
 Series operations
 Modify series
 Series comparisons and iteration
 Series operations
 And much more!
Requirements
 No OS requirement but the tutorials are recorded on a Mac with Google Colab
 No experience necessary
Reviews On Our Python Courses:
 "I know enough Python to be dangerous. Most of the ML classes are so abstract and theoretical that no learning happens. This is the first class where we use concrete examples that I can relate to and allow me to learn. Absolutely love this course!"  Mary T.
 "Yes, this is an amazing start. For someone new in python this is a very simple boot course. I am able to relate to my earlier programming experience with ease!"  Gajendran C.
 "Clear and concise information"  Paul B.
 "Easy to understand and very clear explanations. So far so good!!!"  Alejandro M.
Your Instructor
Nimish Narang is Mammoth Interactive's lead developer specializing in Python, iOS and Android. Primarily a coder, he also is an avid trader.
Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvardโs edX, Business Insider and more.
Over 11 years, Mammoth Interactive has built a global student community with 1.1 million courses sold. Mammoth Interactive has released over 250 courses and 2,500 hours of video content.
Founder and CEO John Bura has been programming since 1997 and teaching
since 2002. John has created topselling applications for iOS, Xbox and
more. John also runs SaaS company Devonian Apps, building
efficiencyminded software for technology workers like you.
Course Curriculum

Start00. Introduction (4:47)

Start01. Intro To Python (5:46)

Start02. Variables (19:34)

Start03. Type Conversion Examples (10:21)

Start04. Operators (7:21)

Start05. Operators Examples (22:09)

Start06. Collections (8:39)

Start07. Lists (11:55)

Start08. Multidimensional List Examples (8:22)

Start09. Tuples Examples (8:51)

Start10. Dictionaries Examples (14:41)

Start11. Ranges Examples (8:46)

Start12. Conditionals (6:58)

Start13. If Statement Examples (10:32)

Start14. If Statement Variants Examples (11:35)

Start15. Loops (7:17)

Start16. While Loops Examples (11:47)

Start17. For Loops Examples (11:35)

Start18. Functions (8:04)

Start19. Functions Examples (9:33)

Start20. Parameters And Return Values Examples (14:08)

Start21. Classes and Objects (11:30)

Start22. Classes Example (13:28)

Start23. Objects Examples (10:10)

Start24. Inheritance Examples (17:43)

Start25. Static Members Example (11:20)

Start26. Summary and Outro (4:23)

StartIntro to Python Slides

StartPython_Language_Basics Code

Start00. Course Intro (5:11)

Start01. Intro to Numpy (6:20)

Start02. Installing Numpy (3:59)

Start03. Creating Numpy Arrays (16:55)

Start04. Creating Numpy Matrices (11:57)

Start05. Getting and Setting Numpy Elements (16:59)

Start06. Arithmetic Operations on Numpy Arrays (11:56)

Start07. Numpy Functions Part 1 (19:13)

Start08. Numpy Functions Part 2 (12:36)

Start09. Summary and Outro (3:01)

StartNumpy_Code

StartNumpy Slides

Start00. Panda Course Introduction (5:43)

Start01. Intro to Pandas (7:55)

Start02. Installing Pandas (5:28)

Start03. Creating Pandas Series (20:34)

Start04. Date Ranges (11:29)

Start05. Getting Elements from Series (19:20)

Start06. Getting Properties of Series (13:04)

Start07. Modifying Series (19:01)

Start08. Operations on Series (11:48)

Start09. Creating Pandas DataFrames (22:57)

Start10. Getting Elements from DataFrames (25:12)

Start11. Getting Properties from DataFrames (17:44)

Start12. Dataframe Modification (36:24)

Start13. DataFrame Operations (20:09)

Start14 DataFrame Comparisons and Iteration (15:35)

Start15. Reading CSVs (12:00)

Start16.Summary and Outro (4:14)

StartpandasPracticeCSV

StartPandas_Code

StartPandas Slides