iCAMP PROFESSIONAL SERIES

Python & AI for Beginners

19-Week Comprehensive Programming Journey

Facilitator:

Sam Iso, AI & Python Specialist

Program Overview

What You'll Learn:

  • Core Python programming fundamentals
  • Web development with Flask/FastAPI
  • Data science with Pandas & NumPy
  • Machine learning with Scikit-learn

Perfect For:

Absolute beginners looking to launch their programming career with in-demand Python and AI skills.

Learning Approach:

Hands-on projects with weekly live coding sessions, real-world applications, and personalized feedback.

Course Syllabus

Module 1: Python Fundamentals (4 Weeks)

Topics Covered:

  • Variables & Syntax
  • Loops & Functions
  • Data Structures

Learning Outcomes:

  • Master Python syntax and variables
  • Implement efficient loops and functions
  • Work with lists, dictionaries, and tuples

Final Project:

Build a simple calculator or task manager application

Module 2: Object-Oriented Programming (3 Weeks)

Topics Covered:

  • Classes & Objects
  • Inheritance
  • Encapsulation

Learning Outcomes:

  • Create and manage Python classes
  • Apply inheritance to extend functionality
  • Implement encapsulation for data protection

Final Project:

Develop an inventory management system using OOP principles

Module 3: Python for Web & Microservices (4 Weeks)

Topics Covered:

  • Flask/FastAPI frameworks
  • RESTful API development
  • Microservices basics

Learning Outcomes:

  • Build web applications with Flask/FastAPI
  • Create and consume REST APIs
  • Understand microservices architecture

Final Project:

Develop a pricing service API or document processor

Module 4: Data Science Essentials (4 Weeks)

Topics Covered:

  • Pandas for data manipulation
  • NumPy for numerical computing
  • Data visualization basics

Learning Outcomes:

  • Clean and transform datasets with Pandas
  • Perform numerical operations with NumPy
  • Create insightful data visualizations

Final Project:

Analyze sales data and generate customer insights report

Module 5: Machine Learning Basics (4 Weeks)

Topics Covered:

  • Scikit-learn fundamentals
  • Supervised learning models
  • Model deployment basics

Learning Outcomes:

  • Train and evaluate ML models
  • Implement recommendation systems
  • Deploy simple ML applications

Final Project:

Build a fraud detection system or recommendation engine

Tools & Assessment

Development Tools

Python 3 Jupyter Notebook VS Code Git Flask/FastAPI Scikit-learn

Assessment Method

  • Weekly coding challenges and quizzes
  • Module-specific practical projects
  • Final capstone project integrating all skills

Start Your AI & Python Journey

Join our next cohort and build in-demand skills from scratch with expert guidance.

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