Udemy - Introduction to Python, Numpy & Pandas by AlgoLab Finance

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[ DevCourseWeb.com ] Udemy - Introduction to Python, Numpy & Pandas by AlgoLab Finance
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1. Python Quick Refresher
    • 1. Introduction to Python.mp4 (5.8 MB)
    • 1. Introduction to Python.srt (1.1 KB)
    • 10. Arithmetic Operators.mp4 (8.0 MB)
    • 10. Arithmetic Operators.srt (2.0 KB)
    • 11. Comparison Operators.mp4 (5.5 MB)
    • 11. Comparison Operators.srt (0.8 KB)
    • 12. Logical Operators.mp4 (12.7 MB)
    • 12. Logical Operators.srt (2.9 KB)
    • 13. Conditional statements.mp4 (8.5 MB)
    • 13. Conditional statements.srt (2.0 KB)
    • 14. Loops.mp4 (14.9 MB)
    • 14. Loops.srt (3.8 KB)
    • 15. Sequences Lists.mp4 (12.3 MB)
    • 15. Sequences Lists.srt (3.3 KB)
    • 16. Sequences Dictionaries.mp4 (10.8 MB)
    • 16. Sequences Dictionaries.srt (2.6 KB)
    • 17. Sequences Tuples.mp4 (8.7 MB)
    • 17. Sequences Tuples.srt (1.2 KB)
    • 18. Functions Built-in Functions.mp4 (6.0 MB)
    • 18. Functions Built-in Functions.srt (0.4 KB)
    • 19. Functions User-defined Functions.mp4 (10.2 MB)
    • 19. Functions User-defined Functions.srt (3.4 KB)
    • 2. Setting up Python.mp4 (15.5 MB)
    • 2. Setting up Python.srt (3.1 KB)
    • 3. What is Jupyter.mp4 (6.1 MB)
    • 3. What is Jupyter.srt (1.0 KB)
    • 4. Anaconda Installation Windows, Mac & Ubuntu.mp4 (31.1 MB)
    • 4. Anaconda Installation Windows, Mac & Ubuntu.srt (5.9 KB)
    • 5. How to implement Python in Jupyter.mp4 (4.5 MB)
    • 5. How to implement Python in Jupyter.srt (0.8 KB)
    • 6. Managing Directories in Jupyter Notebook.mp4 (16.4 MB)
    • 6. Managing Directories in Jupyter Notebook.srt (3.4 KB)
    • 7. InputOutput.mp4 (8.0 MB)
    • 7. InputOutput.srt (2.0 KB)
    • 8. Working with different datatypes.mp4 (6.6 MB)
    • 8. Working with different datatypes.srt (1.1 KB)
    • 9. Variables.mp4 (8.7 MB)
    • 9. Variables.srt (1.9 KB)
    2. Essential python libraries for data science
    • 1. Installing Libraries.mp4 (8.4 MB)
    • 1. Installing Libraries.srt (0.7 KB)
    • 2. Importing Libraries.mp4 (8.7 MB)
    • 2. Importing Libraries.srt (1.7 KB)
    • 3. Pandas Library for Data Science.mp4 (3.0 MB)
    • 3. Pandas Library for Data Science.srt (0.7 KB)
    • 4. NumPy Library for Data Science.mp4 (5.3 MB)
    • 4. NumPy Library for Data Science.srt (0.8 KB)
    • 5. Pandas vs NumPy.mp4 (6.3 MB)
    • 5. Pandas vs NumPy.srt (0.5 KB)
    • 6. Matplotlib Library for Data Science.mp4 (5.7 MB)
    • 6. Matplotlib Library for Data Science.srt (0.5 KB)
    • 7. Seaborn Library for Data Science.mp4 (2.8 MB)
    • 7. Seaborn Library for Data Science.srt (0.3 KB)
    3. Fundamental NumPy Properties
    • 1. Introduction to NumPy arrays.mp4 (7.2 MB)
    • 1. Introduction to NumPy arrays.srt (0.7 KB)
    • 2. Creating NumPy arrays.mp4 (32.6 MB)
    • 2. Creating NumPy arrays.srt (4.5 KB)
    • 3. Indexing NumPy arrays.mp4 (26.6 MB)
    • 3. Indexing NumPy arrays.srt (4.9 KB)
    • 4. Array shape.mp4 (4.3 MB)
    • 4. Array shape.srt (0.5 KB)
    • 5. Iterating Over NumPy Arrays.mp4 (20.3 MB)
    • 5. Iterating Over NumPy Arrays.srt (4.4 KB)
    4. Mathematics for Data Science
    • 1. Basic NumPy arrays zeros().mp4 (8.7 MB)
    • 1. Basic NumPy arrays zeros().srt (1.4 KB)
    • 10. Element wise addition.mp4 (9.0 MB)
    • 10. Element wise addition.srt (1.8 KB)
    • 11. Element wise subtraction.mp4 (6.4 MB)
    • 11. Element wise subtraction.srt (0.8 KB)
    • 12. Element wise multiplication.mp4 (6.1 MB)
    • 12. Element wise multiplication.srt (0.7 KB)
    • 13. Element wise division.mp4 (6.4 MB)
    • 13. Element wise division.srt (1.0 KB)
    • 14. Matrix multiplication.mp4 (8.9 MB)
    • 14. Matrix multiplication.srt (1.5 KB)
    • 15. Statistics.mp4 (10.3 MB)
    • 15. Statistics.srt (2.7 KB)
    • 2. Basic NumPy arrays ones().mp4 (5.5 MB)
    • 2. Basic NumPy arrays ones().srt (0.8 KB)
    • 3. Basic NumPy arrays full().mp4 (3.9 MB)
    • 3. Basic NumPy arrays full().srt (1.1 KB)
    • 4. Adding a scalar.mp4 (8.6 MB)
    • 4. Adding a scalar.srt (1.3 KB)
    • 5. Subtracting a scalar.mp4 (6.7 MB)
    • 5. Subtracting a scalar.srt (0.9 KB)
    • 6. Multiplying by a scalar.mp4 (9.1 MB)
    • 6. Multiplying by a scalar.srt (1.0 KB)
    • 7. Dividing by a scalar.mp4 (8.9 MB)
    • 7. Dividing by a scalar.srt (1.5 KB)
    • 8. Raise to a power.mp4 (5.3 MB)
    • 8. Raise to a power.srt (0.7 KB)
    • 9. Transpose.mp4 (5.3 MB)
    • 9. Transpose.srt (0.8 KB)
    5. Python Pandas DataFrames & Series
    • 1. What is a Python Pandas DataFrame.mp4 (6.4 MB)
    • 1. What is a Python Pandas DataFrame.srt (1.1 KB)
    • 10. Statistical summary of the DataFrame.mp4 (6.6 MB)
    • 10. Statistical summary of the DataFrame.srt (0.5 KB)
    • 11. Slicing rows using bracket operators.mp4 (8.8 MB)
    • 11. Slicing rows using bracket operators.srt (1.4 KB)
    • 12. Indexing columns using bracket operators.mp4 (5.9 MB)
    • 12. Indexing columns using bracket operators.srt (0.9 KB)
    • 13. Boolean list.mp4 (8.1 MB)
    • 13. Boolean list.srt (1.2 KB)
    • 14. Filtering Rows.mp4 (9.2 MB)
    • 14. Filtering Rows.srt (1.5 KB)
    • 15. Filtering rows using & and operators.mp4 (9.4 MB)
    • 15. Filtering rows using & and operators.srt (2.0 KB)
    • 16. Filtering data using loc().mp4 (21.7 MB)
    • 16. Filtering data using loc().srt (3.8 KB)
    • 17. Adding and deleting rows and columns.mp4 (17.3 MB)
    • 17. Adding and deleting rows and columns.srt (3.0 KB)
    • 18. Sorting Values.mp4 (10.7 MB)
    • 18. Sorting Values.srt (1.6 KB)

Description

Introduction to Python, Numpy & Pandas by AlgoLab Finance



https://DevCourseWeb.com

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 67 lectures (1h 56m) | Size: 536.5 MB
Master Python, NumPy & Pandas for Data Science in a fun and interesting manner
What you'll learn:
Learn to use Pandas for Data Analysis
Learn to work with numerical data in Python
Learn statistics and math with Python
Learn how to code in Jupiter Notebook
Learn how to install packages in Python

Requirements
No prior data science knowledge required
No programming experience needed

Description
When it comes to being attractive, data scientists are already there. In a highly competitive job market, it is tough to keep them after they have been hired. People with a unique mix of scientific training, computer expertise, and analytical abilities are hard to find.

Like the Wall Street "quants" of the 1980s and 1990s, modern-day data scientists are expected to have a similar skill set. People with a background in physics and mathematics flocked to investment banks and hedge funds in those days because they could come up with novel algorithms and data methods.



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Udemy - Introduction to Python, Numpy & Pandas by AlgoLab Finance


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636.9 MB
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Udemy - Introduction to Python, Numpy & Pandas by AlgoLab Finance


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