Elite Financial Prediction Toolkit - Python Data Science for Stock Markets
Immerse yourself in the exciting world of stock market data analysis and visualization with our 15-hour masterclass.
Leverage the power of Python, Pandas, NumPy, Seaborn, and Matplotlib to extract and interpret valuable insights from financial data.
Learn to build your own Stock Ticker Dashboard Web App using Python, Dash, and Pandas, keeping you updated with real-time stock information.
Delve into algorithmic trading and create customized investing strategies by combining Python, statistics, and Pandas.
Uncover how machine learning techniques, including Twitter sentiment analysis, can be used to forecast stock trends.
This bundle also offers a beginner-friendly introduction to feature analysis and data science, specifically tailored for the stock market.
Your Instructor
This bundle is a collaborative effort between multiple Mammoth Instructors.
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 Harvard’s edX, Business Insider and more.
Over 14 years, Mammoth Interactive has built a global student community with 6+ million courses sold. Mammoth Interactive has released over 1,000 courses and 5,000 hours of video content.
Founder and CEO John Bura has been programming since 1997 and teaching
since 2002. John has created top-selling applications for iOS, Xbox and
more. John also runs SaaS company Devonian Apps, building
efficiency-minded software for technology workers like you.
Course Curriculum
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Start01 Fetch Stock Data (9:12)
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Start02 Project Preview (3:17)
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Start03 Visualize Price Distribution (9:07)
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Start04 Calculate Daily Return (3:27)
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Start05 Compare Returns Of Different Stocks (10:45)
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Start06 Visualize Standard Deviation And Expected Returns (5:44)
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Start07 Calculate Value At Risk (3:52)
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Start08 Monte Carlo Analysis To Estimate Risk (9:11)
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Start09 Visualize Stock Data Features (7:32)
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StartSource Files
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Start01 Make An API Call (6:18)
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Start02 Project Preview (1:58)
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Start03 Convert Data To A Pandas Dataframe (9:41)
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Start04 Batch API Calls To Improve Performance (11:23)
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Start05 Calculate The Number Of Shares To Buy (7:53)
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Start06 Build An Excel File From The Pandas Dataframe (4:18)
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Start07 Project 2 Preview (2:42)
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Start08 Make An API Call (9:47)
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Start09 Execute A Batch API Call (14:59)
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Start10 Remove Low Momentum Stocks (12:12)
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Start11 Calculate New Number Of Shares To Buy (5:30)
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Start12 Find High Quality Momentum Stocks (11:42)
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Start13 Calculate Momentum Percentiles (14:38)
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Start14 Find The 50 Best Value Stocks (6:58)
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Start15 Calculate New Number Of Shares To Buy (3:24)
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Start16 Build An Excel File (3:41)
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Start17 Project 3 Preview (1:55)
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Start18 Build A Dataframe (5:58)
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Start19 Remove Glamour Stocks (5:01)
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Start20 Calculate The Number Of Shares To Buy (14:36)
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Start21 Build A Composite Of Valuation Metrics (15:22)
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Start22 Clean Dataframe (5:49)
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Start23 Calculate Value Percentiles (4:50)
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Start24 Find The 50 Best Momentum Stocks (8:10)
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Start25 Calculate New Number Of Shares To Buy (5:30)
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StartSource Files