XHORST
06-19-2023, 11:29 AM
[Only registered and activated users can see links] for Finance and Data Science
Language: English | Size:3.41 GB
Genre:eLearning
Files Included :
1 - What does this course cover.mp4 (12.54 MB)
MP4
2 - Disclaimer MUST WATCH.mp4 (10.15 MB)
MP4
3 - How to get the most of this course.mp4 (1.46 MB)
MP4
4 - Any questions or problems Reach out.mp4 (1.65 MB)
MP4
61 - Brief Intro to Streamlit.mp4 (245.99 MB)
MP4
62 - Streamlit Portfolio Analysis Dashboard.mp4 (86.88 MB)
MP4
63 - Streamlit Dashboard showing the Top and Worst SP500 Index performers.mp4 (126.84 MB)
MP4
64 - A Machine Learning Model which potentially outperformed the SP500.mp4 (192.12 MB)
MP4
65 - Least Squares Moving Average Trading Strategy.mp4 (157.25 MB)
MP4
66 - Iterative Approach.mp4 (152.98 MB)
MP4
67 - Vectorized Approach.mp4 (164.13 MB)
MP4
68 - Results Analysis.mp4 (92.19 MB)
MP4
69 - Recap on Matrix Operations Expected return and Portfolio Risk.mp4 (105.3 MB)
MP4
70 - Optimization of Portfolio weights.mp4 (135.68 MB)
MP4
71 - The mighty Intersection between Pandas and SQL.mp4 (23.63 MB)
MP4
72 - How to update an SQL Database with Pandas and SQL.mp4 (117.33 MB)
MP4
73 - Build your own Finance DB using Pandas SQL.mp4 (109.65 MB)
MP4
74 - Build a simple Stock recommendation System with your Finance DB.mp4 (80.41 MB)
MP4
75 - Build an Intraday Stock Price Database with Python and SQL.mp4 (92.77 MB)
MP4
76 - Thank you and something to take along.mp4 (15.61 MB)
MP4
5 - Download Anaconda Set Up Jupyter Notebook.mp4 (26.14 MB)
MP4
6 - Jupyter Notebook Basics.mp4 (6.46 MB)
MP4
10 - Practice Time.mp4 (6.7 MB)
MP4
11 - Arithmetic Operators.mp4 (2.52 MB)
MP4
12 - Comparison Operators Logical Operators.mp4 (7.29 MB)
MP4
13 - Indentations IfStatements.mp4 (11.74 MB)
MP4
14 - Practice Time.mp4 (19.41 MB)
MP4
15 - Lists as objects with methods in Python.mp4 (9.1 MB)
MP4
16 - List Slicing Indexing.mp4 (12.21 MB)
MP4
17 - Difference between lists tuples.mp4 (5.82 MB)
MP4
18 - Dictionaries.mp4 (4.14 MB)
MP4
19 - For loops.mp4 (10.35 MB)
MP4
20 - Combining lists loops List comprehension.mp4 (5.76 MB)
MP4
21 - While loop.mp4 (7.41 MB)
MP4
22 - Practice Time.mp4 (14.28 MB)
MP4
23 - Practice your knowledge with a common Interview question.mp4 (10.68 MB)
MP4
24 - Functions.mp4 (20.76 MB)
MP4
7 - Variables Single Datatypes.mp4 (18.79 MB)
MP4
8 - What you should NEVER do.mp4 (6.12 MB)
MP4
9 - Typecasting User Input.mp4 (33.53 MB)
MP4
25 - Setting up a DataFrame and DataFrame properties.mp4 (11.35 MB)
MP4
26 - Adding columns and using dictionaries for DataFrame initialization.mp4 (13.39 MB)
MP4
27 - New columns based on calculations.mp4 (17.44 MB)
MP4
28 - Data Selection with iloc.mp4 (15.91 MB)
MP4
29 - Data Selection with loc.mp4 (13.13 MB)
MP4
30 - Data Filtering with Boolean Masks and Boolean Indexing.mp4 (20.15 MB)
MP4
31 - Pulling stock prices and OHLC data.mp4 (22.02 MB)
MP4
32 - Quick Recap on what we did in the last chapter.mp4 (16.41 MB)
MP4
33 - Return calculation with shift and pctchange.mp4 (35.91 MB)
MP4
34 - Important functions diff dropna rolling.mp4 (32.47 MB)
MP4
35 - Very important argument axis0 or axis1.mp4 (26.15 MB)
MP4
36 - nlargest and nsmallest.mp4 (12.46 MB)
MP4
37 - Bringing together Dataframes Concat.mp4 (11.41 MB)
MP4
38 - Combining Time Series and OHLC in general.mp4 (38.51 MB)
MP4
39 - Resampling Data.mp4 (22.16 MB)
MP4
40 - Resampling OHLC Data.mp4 (12.27 MB)
MP4
41 - Plotting in Pandas.mp4 (18.54 MB)
MP4
42 - Iterating over a dataframe Iterrows.mp4 (38.61 MB)
MP4
43 - Performance Comparison Iterrows vs Vectorization.mp4 (16.52 MB)
MP4
44 - Return calculation deep dive.mp4 (71.17 MB)
MP4
45 - Practice Task Plot the yearly returns of the SP500.mp4 (2.65 MB)
MP4
46 - Solution to the Practice Task Plot yearly returns of the SP500.mp4 (21.65 MB)
MP4
47 - Portfolio Analysis Introduction.mp4 (3.65 MB)
MP4
48 - Variance Standarddeviation Covariance and Correlation.mp4 (16.57 MB)
MP4
49 - Portfolio Return and Risk.mp4 (12.7 MB)
MP4
50 - Portfolio Expected Return and Portfolio Risk using Python.mp4 (12.84 MB)
MP4
51 - Use the Dot Product to calculate Portfolio Return and Portfolio Risk.mp4 (31.62 MB)
MP4
52 - Application to real data Portfolio of Microsoft Coca Cola and Tesla.mp4 (50.09 MB)
MP4
53 - Efficient Frontier Minimum Variance Portfolio and dominant Portfolios.mp4 (81.58 MB)
MP4
54 - Introduction and the Strategy.mp4 (6.79 MB)
MP4
55 - Coding the Trading Strategy iterative approach.mp4 (121.01 MB)
MP4
56 - Vectorizing the Backtest.mp4 (70.23 MB)
MP4
57 - Crosssectional Momentum Part I Survivorship Bias Handling.mp4 (78.91 MB)
MP4
58 - Crosssectional Momentum Part II Constructing and Backtesting.mp4 (95.58 MB)
MP4
59 - TimeSeries Momentum.mp4 (105.78 MB)
MP4
60 - Backtesting JPMorgans Volatility Index VIX based Strategy.mp4 (147.62 MB)
MP4
[Only registered and activated users can see links] ([Only registered and activated users can see links])
[Only registered and activated users can see links] Python for Finance and Data Science.part1.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part2.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part3.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part4.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part1.rar ([Only registered and activated users can see links] )
Python for Finance and Data Science.part2.rar ([Only registered and activated users can see links] )
Python for Finance and Data Science.part3.rar ([Only registered and activated users can see links] )
Python for Finance and Data Science.part4.rar ([Only registered and activated users can see links] )
[Only registered and activated users can see links] Python for Finance and Data Science.part1.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part2.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part3.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part4.rar ([Only registered and activated users can see links])
Language: English | Size:3.41 GB
Genre:eLearning
Files Included :
1 - What does this course cover.mp4 (12.54 MB)
MP4
2 - Disclaimer MUST WATCH.mp4 (10.15 MB)
MP4
3 - How to get the most of this course.mp4 (1.46 MB)
MP4
4 - Any questions or problems Reach out.mp4 (1.65 MB)
MP4
61 - Brief Intro to Streamlit.mp4 (245.99 MB)
MP4
62 - Streamlit Portfolio Analysis Dashboard.mp4 (86.88 MB)
MP4
63 - Streamlit Dashboard showing the Top and Worst SP500 Index performers.mp4 (126.84 MB)
MP4
64 - A Machine Learning Model which potentially outperformed the SP500.mp4 (192.12 MB)
MP4
65 - Least Squares Moving Average Trading Strategy.mp4 (157.25 MB)
MP4
66 - Iterative Approach.mp4 (152.98 MB)
MP4
67 - Vectorized Approach.mp4 (164.13 MB)
MP4
68 - Results Analysis.mp4 (92.19 MB)
MP4
69 - Recap on Matrix Operations Expected return and Portfolio Risk.mp4 (105.3 MB)
MP4
70 - Optimization of Portfolio weights.mp4 (135.68 MB)
MP4
71 - The mighty Intersection between Pandas and SQL.mp4 (23.63 MB)
MP4
72 - How to update an SQL Database with Pandas and SQL.mp4 (117.33 MB)
MP4
73 - Build your own Finance DB using Pandas SQL.mp4 (109.65 MB)
MP4
74 - Build a simple Stock recommendation System with your Finance DB.mp4 (80.41 MB)
MP4
75 - Build an Intraday Stock Price Database with Python and SQL.mp4 (92.77 MB)
MP4
76 - Thank you and something to take along.mp4 (15.61 MB)
MP4
5 - Download Anaconda Set Up Jupyter Notebook.mp4 (26.14 MB)
MP4
6 - Jupyter Notebook Basics.mp4 (6.46 MB)
MP4
10 - Practice Time.mp4 (6.7 MB)
MP4
11 - Arithmetic Operators.mp4 (2.52 MB)
MP4
12 - Comparison Operators Logical Operators.mp4 (7.29 MB)
MP4
13 - Indentations IfStatements.mp4 (11.74 MB)
MP4
14 - Practice Time.mp4 (19.41 MB)
MP4
15 - Lists as objects with methods in Python.mp4 (9.1 MB)
MP4
16 - List Slicing Indexing.mp4 (12.21 MB)
MP4
17 - Difference between lists tuples.mp4 (5.82 MB)
MP4
18 - Dictionaries.mp4 (4.14 MB)
MP4
19 - For loops.mp4 (10.35 MB)
MP4
20 - Combining lists loops List comprehension.mp4 (5.76 MB)
MP4
21 - While loop.mp4 (7.41 MB)
MP4
22 - Practice Time.mp4 (14.28 MB)
MP4
23 - Practice your knowledge with a common Interview question.mp4 (10.68 MB)
MP4
24 - Functions.mp4 (20.76 MB)
MP4
7 - Variables Single Datatypes.mp4 (18.79 MB)
MP4
8 - What you should NEVER do.mp4 (6.12 MB)
MP4
9 - Typecasting User Input.mp4 (33.53 MB)
MP4
25 - Setting up a DataFrame and DataFrame properties.mp4 (11.35 MB)
MP4
26 - Adding columns and using dictionaries for DataFrame initialization.mp4 (13.39 MB)
MP4
27 - New columns based on calculations.mp4 (17.44 MB)
MP4
28 - Data Selection with iloc.mp4 (15.91 MB)
MP4
29 - Data Selection with loc.mp4 (13.13 MB)
MP4
30 - Data Filtering with Boolean Masks and Boolean Indexing.mp4 (20.15 MB)
MP4
31 - Pulling stock prices and OHLC data.mp4 (22.02 MB)
MP4
32 - Quick Recap on what we did in the last chapter.mp4 (16.41 MB)
MP4
33 - Return calculation with shift and pctchange.mp4 (35.91 MB)
MP4
34 - Important functions diff dropna rolling.mp4 (32.47 MB)
MP4
35 - Very important argument axis0 or axis1.mp4 (26.15 MB)
MP4
36 - nlargest and nsmallest.mp4 (12.46 MB)
MP4
37 - Bringing together Dataframes Concat.mp4 (11.41 MB)
MP4
38 - Combining Time Series and OHLC in general.mp4 (38.51 MB)
MP4
39 - Resampling Data.mp4 (22.16 MB)
MP4
40 - Resampling OHLC Data.mp4 (12.27 MB)
MP4
41 - Plotting in Pandas.mp4 (18.54 MB)
MP4
42 - Iterating over a dataframe Iterrows.mp4 (38.61 MB)
MP4
43 - Performance Comparison Iterrows vs Vectorization.mp4 (16.52 MB)
MP4
44 - Return calculation deep dive.mp4 (71.17 MB)
MP4
45 - Practice Task Plot the yearly returns of the SP500.mp4 (2.65 MB)
MP4
46 - Solution to the Practice Task Plot yearly returns of the SP500.mp4 (21.65 MB)
MP4
47 - Portfolio Analysis Introduction.mp4 (3.65 MB)
MP4
48 - Variance Standarddeviation Covariance and Correlation.mp4 (16.57 MB)
MP4
49 - Portfolio Return and Risk.mp4 (12.7 MB)
MP4
50 - Portfolio Expected Return and Portfolio Risk using Python.mp4 (12.84 MB)
MP4
51 - Use the Dot Product to calculate Portfolio Return and Portfolio Risk.mp4 (31.62 MB)
MP4
52 - Application to real data Portfolio of Microsoft Coca Cola and Tesla.mp4 (50.09 MB)
MP4
53 - Efficient Frontier Minimum Variance Portfolio and dominant Portfolios.mp4 (81.58 MB)
MP4
54 - Introduction and the Strategy.mp4 (6.79 MB)
MP4
55 - Coding the Trading Strategy iterative approach.mp4 (121.01 MB)
MP4
56 - Vectorizing the Backtest.mp4 (70.23 MB)
MP4
57 - Crosssectional Momentum Part I Survivorship Bias Handling.mp4 (78.91 MB)
MP4
58 - Crosssectional Momentum Part II Constructing and Backtesting.mp4 (95.58 MB)
MP4
59 - TimeSeries Momentum.mp4 (105.78 MB)
MP4
60 - Backtesting JPMorgans Volatility Index VIX based Strategy.mp4 (147.62 MB)
MP4
[Only registered and activated users can see links] ([Only registered and activated users can see links])
[Only registered and activated users can see links] Python for Finance and Data Science.part1.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part2.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part3.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part4.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part1.rar ([Only registered and activated users can see links] )
Python for Finance and Data Science.part2.rar ([Only registered and activated users can see links] )
Python for Finance and Data Science.part3.rar ([Only registered and activated users can see links] )
Python for Finance and Data Science.part4.rar ([Only registered and activated users can see links] )
[Only registered and activated users can see links] Python for Finance and Data Science.part1.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part2.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part3.rar ([Only registered and activated users can see links])
Python for Finance and Data Science.part4.rar ([Only registered and activated users can see links])