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Course Contents (0/44)
Python Essentials for Data Analytics
Micro Free Courses
Python Essentials for Data Analytics
44 lessons
1. PYTHON SETUP & ENVIRONMENT
Video lesson
1. Installing Python
4m
Video lesson
2. Installing Jupyter Notebook
3m
Reading
3. Setting Up Your Python Environment (VS Code, venvs & pip)
4m
2. PYTHON FUNDAMENTALS
Video lesson
1. Python Variables
2m
Video lesson
2. Python Basic Datatypes
9m
Interactive tutorial
3. QUIZ: Variables & Datatypes
6m
Video lesson
4. Python Lists
3m
Video lesson
5. Python Dictionaries
8m
Reading
6. List Comprehensions & Advanced Collections
4m
Interactive tutorial
7. QUIZ: Lists & Dictionaries
6m
Project submission
8. ASSIGNMENT: Lists & Dict
32m
Video lesson
9. Python For Loops
5m
Video lesson
10. Python While Loops
7m
Interactive tutorial
11. QUIZ: For & While Loops
6m
Video lesson
12. Python If Conditions
8m
Video lesson
13. Python Functions
14m
Project submission
14. ASSIGNMENT: Loops, if conditions & functions
31m
Video lesson
15. Python Strings
17m
Reading
16. Text Wrangling Essentials: split, join, and formatting
3m
Video lesson
17. Python Regular Expressions (Regex)
6m
Interactive tutorial
18. QUIZ: Python Fundamentals
17m
Project submission
19. ASSIGNMENT: Python Fundamentals
32m
3. NUMPY FOUNDATIONS
Video lesson
1. NumPy vs Python Lists
11m
Video lesson
2. NumPy Basics
14m
Interactive tutorial
3. QUIZ: Numpy Basics
12m
Video lesson
4. NumPy Broadcasting
6m
Video lesson
5. NumPy Aggregations
4m
Reading
6. NumPy Vectorization, Boolean Masks & Statistical Aggregations
4m
Interactive tutorial
7. QUIZ: Numpy Foundations
18m
Project submission
8. ASSIGNMENT: NumPy Foundations
32m
4. PANDAS FOR DATA ANALYTICS
Video lesson
1. DataFrame & Series Basics: Selecting Rows and Columns
34m
Video lesson
2. Reading & Writing Data
33m
Interactive tutorial
3. QUIZ: Basics
6m
Video lesson
4. Filtering & Sorting
6m
Video lesson
5. Handling Missing Values
4m
Reading
6. Mastering Pandas Data Cleaning: dropna, fillna, and Type Casting
3m
Video lesson
7. Working with Date & Time
10m
Interactive tutorial
8. QUIZ: Basic Filtering, etc.
9m
Project submission
9. ASSIGNMENT: Pandas Basics
32m
Video lesson
10. Combining DataFrames: SQL-Style Relational Merges
8m
Video lesson
11. Groupby & Aggregations
11m
Reading
12. Essential Pandas Wrangling: Merging, GroupBy Best Practices & reset_index
3m
Interactive tutorial
13. QUIZ: Pandas Module
14m
Project submission
14. ASSIGNMENT: Pandas Module
32m
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QUIZ: Basics
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QUIZ: Basics
6 minutes
Interactive tutorial
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In the context of the Pandas library, which of the following best describes a Series?
It represents a 3-dimensional array of data.
It is a 1-dimensional labeled array capable of holding any data type.
It is strictly a 2-dimensional table with rows and columns.
It is a mutable list that cannot contain duplicate values.
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