Udemy - Python for Data Science Bootcamp Course - Beginner to Advanced

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[ FreeCourseWeb.com ] Udemy - Python for Data Science Bootcamp Course - Beginner to Advanced
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1. Introduction
    • 1. Introduction.mp4 (8.1 MB)
    • 1. Introduction.srt (2.1 KB)
    • 2. Installing Python on Jupyter.mp4 (3.2 MB)
    • 2. Installing Python on Jupyter.srt (0.9 KB)
    • 3. Installing and Running Python on Jupyter.mp4 (2.1 MB)
    • 3. Installing and Running Python on Jupyter.srt (0.9 KB)
    • 4. Installing Pandas on Jupyter.mp4 (5.1 MB)
    • 4. Installing Pandas on Jupyter.srt (1.3 KB)
    2. Python Basics
    • 1. Introduction to Python Data Types.mp4 (2.3 MB)
    • 1. Introduction to Python Data Types.srt (0.7 KB)
    • 10. Coding Lists in Python.mp4 (137.8 MB)
    • 10. Coding Lists in Python.srt (11.5 KB)
    • 11. Dictionaries in Python.mp4 (4.3 MB)
    • 11. Dictionaries in Python.srt (1.1 KB)
    • 12. Coding Dictionaries in Python.mp4 (157.7 MB)
    • 12. Coding Dictionaries in Python.srt (11.8 KB)
    • 13. Tuples in Python.mp4 (1.9 MB)
    • 13. Tuples in Python.srt (0.8 KB)
    • 14. Coding Tuples in Python - Part 1.mp4 (33.6 MB)
    • 14. Coding Tuples in Python - Part 1.srt (3.9 KB)
    • 15. Coding Tuples in Python - Part 2.mp4 (33.7 MB)
    • 15. Coding Tuples in Python - Part 2.srt (5.4 KB)
    • 16. Sets in Python.mp4 (3.0 MB)
    • 16. Sets in Python.srt (0.9 KB)
    • 17. Coding Sets in Python.mp4 (99.5 MB)
    • 17. Coding Sets in Python.srt (8.2 KB)
    • 18. Coding Type Conversion.mp4 (12.4 MB)
    • 18. Coding Type Conversion.srt (2.3 KB)
    • 19. Coding Booleans in Python.mp4 (16.2 MB)
    • 19. Coding Booleans in Python.srt (2.6 KB)
    • 2. Coding Introduction to Python Data Types.mp4 (38.5 MB)
    • 2. Coding Introduction to Python Data Types.srt (4.3 KB)
    • 20. Input Output in Python.mp4 (4.5 MB)
    • 20. Input Output in Python.srt (1.2 KB)
    • 21. Coding Input Output in Python.mp4 (18.7 MB)
    • 21. Coding Input Output in Python.srt (2.2 KB)
    • 22. Files in Python.mp4 (7.4 MB)
    • 22. Files in Python.srt (1.5 KB)
    • 23. Coding Files in Python.mp4 (23.9 MB)
    • 23. Coding Files in Python.srt (3.8 KB)
    • 24. Introduction to Functions.mp4 (7.4 MB)
    • 24. Introduction to Functions.srt (1.6 KB)
    • 25. Coding Constructors.mp4 (10.2 MB)
    • 25. Coding Constructors.srt (2.2 KB)
    • 26. Tuple Unpacking with Python Functions.mp4 (3.0 MB)
    • 26. Tuple Unpacking with Python Functions.srt (0.8 KB)
    • 27. Coding Tuple Unpacking with Python Functions.mp4 (7.8 MB)
    • 27. Coding Tuple Unpacking with Python Functions.srt (2.0 KB)
    • 3. Introduction to Strings.mp4 (1.8 MB)
    • 3. Introduction to Strings.srt (0.9 KB)
    • 4. Coding Introduction to Strings.mp4 (6.5 MB)
    • 4. Coding Introduction to Strings.srt (1.3 KB)
    • 5. Indexing and Slicing with Strings.mp4 (2.3 MB)
    • 5. Indexing and Slicing with Strings.srt (0.8 KB)
    • 6. Coding Indexing and Slicing with Strings.mp4 (8.6 MB)
    • 6. Coding Indexing and Slicing with Strings.srt (1.8 KB)
    • 7. String Methods.mp4 (15.6 MB)
    • 7. String Methods.srt (3.0 KB)
    • 8. Coding String Methods.mp4 (84.9 MB)
    • 8. Coding String Methods.srt (11.8 KB)
    • 9. Lists in Python.mp4 (4.2 MB)
    • 9. Lists in Python.srt (1.2 KB)
    3. Advanced Python
    • 1. Closures in Python.mp4 (3.8 MB)
    • 1. Closures in Python.srt (1.1 KB)
    • 10. Decorators in Python.mp4 (7.1 MB)
    • 10. Decorators in Python.srt (1.5 KB)
    • 11. Coding Decorators in Python.mp4 (38.3 MB)
    • 11. Coding Decorators in Python.srt (4.5 KB)
    • 12. Memoization using decorators.mp4 (4.0 MB)
    • 12. Memoization using decorators.srt (1.1 KB)
    • 13. Coding Memoization using decorators.mp4 (12.5 MB)
    • 13. Coding Memoization using decorators.srt (2.5 KB)
    • 14. Generators in Python.mp4 (12.8 MB)
    • 14. Generators in Python.srt (2.1 KB)
    • 15. Coding Generators in Python.mp4 (18.0 MB)
    • 15. Coding Generators in Python.srt (3.1 KB)
    • 16. Coding Generator Expressions.mp4 (36.8 MB)
    • 16. Coding Generator Expressions.srt (3.2 KB)
    • 17. Coroutine in Python.mp4 (4.6 MB)
    • 17. Coroutine in Python.srt (1.2 KB)
    • 18. Coding Coroutine in Python.mp4 (17.2 MB)
    • 18. Coding Coroutine in Python.srt (2.5 KB)
    • 19. Filter and Reduce Functions.mp4 (8.3 MB)
    • 19. Filter and Reduce Functions.srt (1.8 KB)
    • 2. Coding Closures in Python.mp4 (10.3 MB)
    • 2. Coding Closures in Python.srt (2.3 KB)
    • 20. Coding Filter and Reduce Functions.mp4 (33.5 MB)
    • 20. Coding Filter and Reduce Functions.srt (4.6 KB)
    • 21. Coding Itertools in Python Part 1.mp4 (21.1 MB)
    • 21. Coding Itertools in Python Part 1.srt (2.1 KB)
    • 22. Coding Itertools in Python Part 2.mp4 (62.1 MB)
    • 22. Coding Itertools in Python Part 2.srt (8.6 KB)
    • 23. Efficient Code and Optimization techniques for Python.mp4 (13.5 MB)
    • 23. Efficient Code and Optimization techniques for Python.srt (2.6 KB)
    • 24. Coding Efficient Code and Optimization techniques for Python.mp4 (152.1 MB)
    • 24. Coding Efficient Code and Optimization techniques for Python.srt (15.4 KB)
    • 3. Packing and Unpacking Arguments.mp4 (6.2 MB)
    • 3. Packing and Unpacking Arguments.srt (1.4 KB)
    • 4. Coding Packing and Unpacking Arguments.mp4 (28.1 MB)
    • 4. Coding Packing and Unpacking Arguments.srt (3.0 KB)
    • 5. Lambda functions in Python.mp4 (3.3 MB)
    • 5. Lambda functions in Python.srt (1.1 KB)
    • 6. Coding Lambda functions in Python.mp4 (11.1 MB)
    • 6. Coding Lambda functions in Python.srt (2.2 KB)
    • 7. Map and Filter Functions.mp4 (5.0 MB)
    • 7. Map and Filter Functions.srt (1.2 KB)
    • 8. Coding Map Function.mp4 (17.7 MB)
    • 8. Coding Map Function.srt (2.4 KB)
    • 9. Coding Filter Function.mp4 (9.9 MB)

Description

Python for Data Science Bootcamp Course:Beginner to Advanced



https://FreeCourseWeb.com

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.16 GB | Duration: 7h 25m
Master Everything you need to know about Python, Pandas and Numpy with Code Implementations, Examples and many more!
What you'll learn
Master Everything you need to know about Python, Pandas and Numpy with Code Implementations, Examples and many more!
Learn Advanced Python modules and complex features such as Python Decorators, Generators, Comprehensions, Regular Expressions, Map, Filter functions, collection
Build a solid beginner-level understanding of the Python programming language by learning and coding simultaneously with Instructor.
Build thorough Python Object-Oriented Programming (OOP) skills.
Learn how to give structure to the program with Functions.
Learn Constructor, destructor, private variables, Inheritance, Polymorphism, Abstraction with Example
Implement and call methods. Understand their purpose within classes.
Define instance attributes and class attributes.
Define logic using conditional statements, looping.
Hands-On Implementations and Exercises( Code with Instructor simultaneously).
Gain a deep and hands-on understanding of pandas data structures.
Learn Series at a Glance - Series Methods and Handling
Implement DataFrames in depth
Implement GroupBy, Slicing, Aggregates and Reshaping With Pivots
Join, Melt, cut, transform, clean, filter, groupby, pivot, merge and otherwise manipulate any dataset.
Practice reading data from the web, pickles, Excel files right within pandas.
Implement advance Pandas DataFrame manipulations: multiIndexing, stacking, hierarchical indexing, pivoting, melting and more.
Import, clean, and merge messy Data and prepare Data for Machine Learning
Merge and Concatenate many Datasets efficiently.
Scale and Automate data merging
Clean and format data easily.
Detect and intelligently fill missing values.
Group, aggregate and summarise your data.
Implement important methods, attributes, and techniques to manipulate data in pandas and python.
Learn to use NumPy for Numerical Data
Learn basic and advanced features in NumPy (Numerical Python)
Learn and practice all relevant Pandas methods and workflows with Real-World Datasets
Understand how to use both the Jupyter Notebook and create .py files.
Acquire the pre-requisite Python skills to move into different areas - Machine Learning, Data Science, Backend Development etc.
Have the skills and understanding of Python, Pandas and Numpy to confidently apply for Python programming jobs at Tech companies.

Description
Harvard University has named a data scientist as the ‘sexiest job title of the 21st century’. For the last 5 years, data science has been featured as a top career by Glassdoor. Data scientists are responsible for finding, filtering, and organizing data for companies. They explore through large piles of data generated every single day to find patterns that will benefit an organization, and at the same time, help to fulfill their strategic goals. This course covers everything you need to know in order to become a brilliant data scientist.

Topics Covered in this course (in depth):

Build a solid beginner-level understanding of the Python programming language by learning and coding simultaneously with Instructor.



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Udemy - Python for Data Science Bootcamp Course - Beginner to Advanced


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2.2 GB
seeders:5
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Udemy - Python for Data Science Bootcamp Course - Beginner to Advanced


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