The 2025 Data & Cloud Mastery Course Bundle
What's Included

Efficient Coding in Python
- Experience level required: All levels
- Access 73 lectures & 15 hours of content 24/7
- Length of time users can access this course: Lifetime
Course Curriculum
73 Lessons (15h)
- Your First Program 
- Google Colab Google Colab - Part 117:36Google Colab - Part 24:43
- How to read a file in Google Colab How to read a file in Google Colab4:51
- Anaconda Installation Anaconda Installation - 6: 53
- How to read a file in Jupyter Notebook How to read a file in Jupyter Notebook3:57
- Introduction to Sets Introduction to Sets6:23
- Introduction to Lists Introduction to Lists6:37
- Introduction to Dictionaries Introduction to Dictionaries9:01
- Introduction to Recursion Introduction to Recursion4:19
- Introduction to Tuples Introduction to Tuples6:18
- Introduction to Web Scrapping Introduction to Web Scrapping16:42
- Accessing Arrays Accessing Arrays6:36
- Accessing and Methods in Tuples Accessing and Methods in Tuples7:26
- Accessing Dictionaries Accessing Dictionaries4:45
- Accessing Lists Accessing Lists8:03
- Axis-Wise Operations Axis-Wise Operations4:56
- Beautiful Soup Introduction and Explanation Beautiful Soup Introduction and Explanation20:37
- Beautiful Soup GetElementsBy Id and Multiple Tag Beautiful Soup GetElementsBy Id and Multiple Tag - Part 110:23Beautiful Soup GetElementsBy Id and Multiple Tag - Part 226:53Beautiful Soup GetElementsBy Id and Multiple Tag - Part 316:24Beautiful Soup GetElementsBy Id and Multiple Tag - Part 415:32
- Boolean Indexing Boolean Indexing5:17
- Break and Continue Statement Break and Continue Statement9:58
- Broadcasting and Stacking Broadcasting and Stacking9:14
- Classes & Instances Classes & Instances10:17
- Classes & Instances Creation Classes & Instances Creation12:13
- Conditionals Conditionals8:18
- Constructors or Instantiators Constructors or Instantiators8:32
- Creating Arrays Creating Arrays9:25
- Creating Dictionaries Creating Dictionaries8:44
- Creating Lists Creating Lists8:48
- Creating Sets Creating Sets4:07
- Creating Tuples Creating Tuples4:57
- Data Structures - Scalars, Vectors, and Matrix Data Structures - Scalars, Vectors, and Matrix10:41
- Data Structures Data Structures6:52
- Data Types - Integer Data Types - Integer
- Data Types - Boolean Data Types - Boolean7:37
- Data Types - Float Data Types - Float5:19
- Data Types - String Data Types - String11:28
- Elementwise Operations Elementwise Operations6:42
- Else & Elif Statement Else & Elif Statement8:52
- Expression Evaluation Expression Evaluation12:39
- For Loop with Range For Loop with Range11:06
- For Loop with Variables For Loop with Variables6:28
- Functions Functions10:13
- Functions in Numpy Functions in Numpy8:55
- Functions with Arguments Functions with Arguments8:09
- Functions with Multiple Arguments Functions with Multiple Keyword Arguments8:53
- Functions without Arguments Functions without Arguments9:14
- If Statements If Statements8:31
- Indexing and Slicing In Strings Indexing and Slicing In Strings13:54
- Inheritance Inheritance8:28
- Input, Output and Formatting Input, Output and Formatting11:14
- Jupyterv2 Jupyterv25:33
- Logical Operations in Conditionals Logical Operations in Conditionals11:20
- Loops Loops5:02
- Methods In Dictionaries Methods In Dictionaries14:00
- Methods In List Methods In List - Part 113:06Methods In List - Part 210:11
- Methods In Sets Methods In Sets - Part 18:26Methods In Sets - Part 27:29
- Nested If Statements Nested If Statements14:03
- Numerical Python Numerical Python6:17
- Polymorphism Polymorphism7:17
- PyMySQL Introduction PyMySQL Introduction10:56
- PyMySQL PyMySQL - Part 142:19PyMySQL - Part 251:25PyMySQL - Part 340:34
- Python Request Library Python Request Library10:45
- Python Properties and Applications Python Properties and Applications18:08
- Recursion - Summation Function Part 1 Recursion - Summation Function Part 15:13
- Recursionipynb - Summation Function Part 2 Recursionipynb - Summation Function Part_24:58
- Recursion- Base Case Recursion- Base Case5:13
- Regular Expressions Regular Expressions34:45
- Scope of a Function Scope of a Function7:08
- Single and Multi-Line Commenting Single and Multi-Line Commenting6:51
- String Access Using Loops String Access Using Loops7:14
- The Self Method The Self Method6:09
- Understanding Programming Understanding Programming15:18
- Variables and Values Variables and Values9:42
- While While8:46
- Quiz Quiz
Efficient Coding in Python
GreyCampus | EdTech Platform
GreyCampus helps people power their careers through skills and certifications. They strongly advocate for continuous upskilling and the acquisition of certifications as crucial to maintaining long-term success in one's career. As older skills rapidly lose relevance, the demand for newer, sought-after skills is rapidly increasing. GreyCampus firmly believes that staying skilled will keep you ahead in your career.
Description
Master Python Techniques for Efficient Programming
This course is designed to help you master the art of writing optimized and elegant Python code. You’ll start by learning the basics, such as using Python IDEs and understanding fundamental programming concepts like data types, conditional statements, and loops. As you advance, you'll explore functions, recursion, regular expressions, and data structures. The course also covers arrays and introduces you to the powerful NumPy library, ensuring you have the tools to apply efficient coding techniques in real-world Python projects.
What you'll learn
- Access 73 lectures & 15 hours of content 24/7
- Learn file handling in Google Colab and Jupyter Notebook
- Install and set up Anaconda for Python development
- Master Python data structures: lists, dictionaries, sets, and tuples
- Understand recursion and apply it in real-world coding scenarios
- Perform web scraping with Beautiful Soup
- Explore advanced Python features: boolean indexing, broadcasting, and stacking
- Master control flow with conditionals, loops, and recursion
- Dive into object-oriented programming: classes, instances, and inheritance
- Use PyMySQL for database management in Python
- Perform operations using NumPy for numerical computing
- Work with regular expressions, string manipulation, and functional programming
Who is this course for
- Anyone looking to learn Python from scratch or enhance their existing skills
- Anyone interested in mastering data structures and algorithms in Python
- Anyone who wants to explore web scraping and database management using Python
Specs
Important Details
- Length of time users can access this course: lifetime
- Access options: desktop & mobile
- Redemption deadline: redeem your code within 30 days of purchase
- Experience level required: all levels
- Certificate of Completion ONLY
- Updates included
- Closed captioning NOT available
- NOT downloadable for offline viewing
- Have questions on how digital purchases work? Learn more here
- Learn more about our Lifetime deals here!
Requirements
- 
No prior programming experience is required, but familiarity with basic concepts may be helpful 

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Terms
- Unredeemed licenses can be returned for store credit within 30 days of purchase. Once your license is redeemed, all sales are final.