My Certificates


Python 3 Specialization

Python 3 Programming

(University of Michigan)

The specialization has 5 courses:

  1. Python Basics
  2. Python Functions, Files, and Dictionaries
  3. Data Collection and Processing with Python
  4. Python Classes and Inheritance
  5. Capstone Project


Python for Everybody

Python for Everybody

(University of Michigan)

The specialization has 5 courses:

  1. Programming for Everybody
  2. Python Data Structures
  3. Using Python to Access Web Data
  4. Using Databases with Python
  5. Capstone Project


Google Professional Workspace Administrator

Google Professional Workspace Administrator

(Google Cloud)

The specialization has 5 courses:

  1. Introduction to Google Workspace Administration
  2. Managing Google Workspace
  3. Google Workspace Security
  4. Google Workspace Mail Management


C++ For C Programmers, Part A

C++ For C Programmers, Part A

(University of California, Santa Cruz)

Concepts learnt from the course:

  1. Migration from C language to CPP
  2. CPP Functions and Generics, Classes (OOPs)
  3. Types of Constructors, Dynamic Memory Allocation
  4. Prim's and Kruskal's algorithms
  5. Use of basic Container Classes, Algorithms


C++ For C Programmers, Part B

C++ For C Programmers, Part B

(University of California, Santa Cruz)

Concepts learnt from the course:

  1. STL and the game of Hex
  2. Hex as a graph and Inheritance
  3. Hex and the use of AI and C++ Move semantics
  4. Monte Carlo Hex Program
  5. Further advanced C++ Topics and Patterns


Object-Oriented Data Structures in C++

Object-Oriented Data Structures in C++

(University of Illinois at Urbana-Champaign)

Concepts learnt from the course:

  1. Orientation and Writing a C++ Program
  2. Understanding the C++ Memory Model
  3. Developing C++ Classes
  4. Engineering C++ Software Solutions
  5. Some more Advanced Concepts


Object Oriented Programming in Java

Object Oriented Programming in Java

(University of California San Diego)

Concepts learnt from the course:

  1. Memory Models and Scope
  2. Graphical output: Creating GUIs and Displaying Data
  3. Diffenet Types of Inheritances
  4. GUIs: Responding to User Events
  5. Searching and Sorting Algorithms


Operating Systems and You: Becoming a Power User

Operating Systems and You: Becoming a Power User

(Google)

Concepts learnt from the course:

  1. Navigating the System
  2. Users and Permissions
  3. Package and Software Management
  4. File Systems and Process Management
  5. Operating Systems in Practice


What is Data Science?

What is Data Science?

(IBM)

Concepts learnt from the course:

  1. Defining Data Science and What Data Scientists Do
  2. Data Science Topics
  3. Data Science in Business
  4. What after Data Science



Python for Data Science, AI & Development

Python for Data Science, AI & Development

(IBM)

Concepts learnt from the course:

  1. Python Basics
  2. Python Data Structures
  3. Python Programming Fundamentals
  4. Working with Data in Python
  5. APIs, and Data Collection


Tools for Data Science

Tools for Data Science

(IBM)

Concepts learnt from the course:

  1. Data Scientist's Toolkit
  2. Open Source Tools
  3. IBM Tools for Data Science
  4. Jupyter Notebook Assignments



Machine Learning with Python

Machine Learning with Python

(IBM)

Concepts learnt from the course:

  1. Introduction to Machine Learning
  2. Regression
  3. Classification
  4. Clustering
  5. Recommender Systems


Programming in C++

Programming in C++

(NPTEL - IIT Kharagpur)

Concepts learnt from the course:

  1. Introduction to Programming in C++
  2. C++ : C with Classes
  3. Overview of OOPs
  4. Ingeritance and Polymorphism
  5. Exception Handling in C++
  6. Standard Template Library (STL) in C++


Python for Data Science

Python for Data Science

(NPTEL - IIT Madras)

Concepts learnt from the course:

  1. Introduction to Python IDE - Spyder
  2. Python Data Types and Associated Operations
  3. Introduction to Matplotlib and Seaborn Libraries
  4. Introduction to Pandas Dataframes
  5. Regression Case Study
  6. Classification Case Study