teaching

Comprehensive teaching materials and workshops for Python, Machine Learning, and Full-Stack Development

Teaching Philosophy

I believe in hands-on, project-based learning that bridges theory and practice. My teaching materials emphasize practical application, real-world projects, and building a strong foundation in programming fundamentals. All course materials are open-source and freely available on GitHub.

📚 Workshop Repository

Visit my comprehensive Workshop Repository for all teaching materials.

🐍 Complete Python Bootcamp

A comprehensive Python programming course for beginners to intermediate learners.

Repository: Complete-Python-Bootcamp

Course Structure

Fundamentals

  • Numbers, Strings, and Print Formatting
  • Lists, Dictionaries, Tuples, Sets, and Booleans
  • Object and Data Structures Assessment
  • Comparison Operators and Chained Comparisons

Control Flow & Functions

  • if/else statements, Loops, Range
  • List Comprehensions
  • Methods and Functions
  • Lambda Expressions
  • Nested Statements and Scope
  • Function and Method Homework Assignments

Object-Oriented Programming

  • Classes and Objects
  • Inheritance and Polymorphism
  • Special Methods
  • Errors and Exception Handling
  • OOP Homework Assignments

Advanced Topics

  • Modules and Packages
  • Built-in Functions (map, reduce, filter, zip, enumerate, all(), any())
  • Decorators
  • Generators and Iterators
  • Collection Modules
  • Math, Datetime, and Regular Expression Modules
  • Python Debugger and Code Timing
  • StringIO and Advanced Data Structures

GUI Development

  • Introduction to Graphical User Interfaces
  • Jupyter Widgets
  • Widget Events and Styling
  • Dashboard Creation

Capstone Projects

  • Milestone Project 1: Tic-Tac-Toe Game
  • Milestone Project 2: Blackjack Game
  • Final Capstone Projects: 100+ project ideas with solutions

Target Audience

  • Complete beginners to Python
  • Students preparing for data science careers
  • Developers looking to strengthen Python fundamentals

🤖 Python for Data Science & Machine Learning Bootcamp

Advanced course focusing on data analysis, visualization, and machine learning.

Repository: Refactored_Py_DS_ML_Bootcamp

Course Structure

Python Crash Course

  • Intensive Python review for data science
  • Exercises and assessments

Data Analysis with NumPy & Pandas

  • NumPy Arrays and Operations
  • Pandas DataFrames and Series
  • Data Indexing, Selection, and Operations
  • Missing Data Handling
  • GroupBy Operations
  • Merging, Joining, and Concatenating

Data Visualization

  • Matplotlib: Line plots, scatter plots, histograms, heatmaps
  • Seaborn: Distribution plots, categorical plots, matrix plots, grids
  • Plotly & Cufflinks: Interactive visualizations
  • Geographical Plotting: Choropleth maps

Data Capstone Projects

  • 911 Calls Data Analysis: Comprehensive EDA and visualization
  • Finance Data Analysis: Stock market analysis
  • Real-world datasets and challenges

Machine Learning

Supervised Learning:

  • Linear Regression
  • Logistic Regression
  • K-Nearest Neighbors (KNN)
  • Decision Trees and Random Forests
  • Support Vector Machines (SVM)
  • Naive Bayes Classification

Unsupervised Learning:

  • K-Means Clustering
  • Principal Component Analysis (PCA)
  • Hierarchical Clustering

Advanced Topics:

  • Natural Language Processing (NLP)
  • Recommender Systems (Collaborative & Content-Based Filtering)
  • Time Series Analysis
  • Deep Learning Fundamentals
  • TensorFlow Basics

Projects Included

  • Stock Price Forecasting
  • Customer Segmentation
  • Movie Recommendation System
  • Sentiment Analysis
  • Breast Cancer Detection
  • College Clustering Analysis
  • Loan Default Prediction

Target Audience

  • Intermediate Python programmers
  • Aspiring data scientists and ML engineers
  • Students preparing for industry roles

🌐 Full-Stack Web Development

Complete course covering frontend and backend web development.

Repository: Full Stack WEB DEV

Course Structure

Frontend Development

  • HTML5: Semantic markup, forms, multimedia
  • CSS3: Styling, layouts, Flexbox, Grid, animations
  • JavaScript:
    • Variables, data types, operators
    • Control flow and loops
    • Functions and scope
    • Arrays and array methods
    • DOM manipulation
    • Events and event handling
    • Asynchronous JavaScript (Promises, async/await)

Backend Development (Coming Soon)

  • Python/Django: Web frameworks and REST APIs
  • Node.js: Server-side JavaScript
  • Database Integration: SQL and NoSQL databases
  • Authentication: User management and security

Projects

  • Responsive portfolio websites
  • Interactive web applications
  • To-do list applications
  • Calculator and game projects

Target Audience

  • Complete beginners to web development
  • Students looking to build full-stack applications
  • Developers transitioning to web technologies

📖 Teaching Materials Features

✅ Comprehensive Jupyter Notebooks

  • Step-by-step code examples
  • Detailed explanations and comments
  • Visual outputs and data visualizations
  • Practice exercises and solutions

✅ Project-Based Learning

  • Real-world capstone projects
  • 100+ practice project ideas
  • Progressive difficulty levels
  • Solution files for reference

✅ Assessments & Homework

  • Multiple choice quizzes
  • Coding assignments
  • Project milestones
  • Self-assessment tools

✅ Open-Source & Free

  • All materials available on GitHub
  • Regular updates and improvements
  • Community-driven learning
  • Fork, modify, and contribute

🎯 Learning Paths

Path 1: Complete Beginner to Python Developer

  1. Complete Python Bootcamp (Fundamentals)
  2. Complete Python Bootcamp (OOP & Advanced Topics)
  3. Capstone Projects

Path 2: Python to Data Science

  1. Python Crash Course
  2. NumPy & Pandas
  3. Data Visualization (Matplotlib, Seaborn, Plotly)
  4. Machine Learning Algorithms
  5. Data Science Capstone Projects

Path 3: Web Development Specialist

  1. HTML & CSS Fundamentals
  2. JavaScript Programming
  3. Full-Stack Development
  4. Web Projects & Deployment

📊 Teaching Experience

Wirral Met College (2024-2025)

  • Computer Science Professor
  • Taught Python programming and web development
  • Developed hands-on curriculum and lab materials
  • Mentored students on real-world projects

University of Liverpool (2023-2024)

  • Teaching Assistant for Software Engineering and Cybersecurity modules
  • Guided undergraduate students through coursework and projects
  • Conducted tutorial sessions and lab supervision

Coursera (2017-2020)

  • Remote Student Mentor Volunteer
  • Mentored global students in computer science fundamentals
  • Provided guidance on projects and career development

🚀 Student Success

My teaching materials have been used by students worldwide to:

  • Transition into data science and ML roles
  • Build professional portfolios and projects
  • Prepare for technical interviews
  • Launch freelance careers
  • Contribute to open-source projects

💡 Get Started

  1. Visit the Workshop Repository
  2. Clone or download the course materials
  3. Follow the README instructions in each course folder
  4. Work through notebooks sequentially
  5. Complete projects and build your portfolio
  6. Join the community and contribute back

📬 Support & Contact

Have questions or need help with the materials?

🌟 All-In-One Workshop Access

Special Offer: Access to all workshop materials for Rs 999

  • Complete Python Bootcamp
  • Data Science & Machine Learning
  • Full-Stack Web Development
  • Future workshops (Computer Vision, MATLAB, Adobe Suite)

For enrollment details, email: aakashm301@gmail.com

“The best way to learn programming is by doing. These materials are designed to get you coding from day one.”