3-day Virtual Seminar

Introduction to AI and Machine Learning: Foundations, Skills, and Career Opportunities

Overview

This webinar provides a structured and practical introduction to Artificial Intelligence and Machine Learning for students and professionals from diverse backgrounds. Starting with the fundamentals of AI, the session explains why Machine Learning is central to modern AI systems and how Computer Science skills such as Python programming, data handling, and mathematical thinking enable ML solutions.

Participants will gain conceptual clarity on how ML models work, understand common learning paradigms such as classification and regression, explore key algorithms, and learn how these skills align with current industry roles and career paths.

Why you should Attend

• AI is no longer optional - professionals without Machine Learning knowledge risk falling behind in a job market that increasingly demands data-driven and intelligent systems expertise
  
• This webinar helps you understand what skills truly matter and how AI and ML fit into today’s technology landscape before it’s too late to catch up
  

Areas Covered in the Session

• What is Artificial Intelligence and where does Machine Learning fit?
  
• Why Machine Learning is essential in today’s data-driven world
  
• Core Computer Science skills required for ML (Python, programming fundamentals)
  
• Understanding how Machine Learning models learn from data
  
• Types of ML problems: classification and regression
  
• Overview of key ML algorithms:
  
  • Linear Regression
    
  • Decision Trees
    
  • Logistic Regression
    
• Overview of Bayesian Networks
  
• Bayesian model vs BlackBox ML models
  
• Mathematical intuition behind ML:
  
  • Optimization and gradient descent
    
  • Role of probability and statistics
    
• Introduction to Neural Networks and deep learning concepts
  
• Machine Learning in the current job market
  
• Career paths and roles after learning ML fundamentals

Who Will Benefit

• Computer Science Students
  
• Engineering Students (any discipline)
  
• Software Developers
  
• Aspiring Data Scientists
  
• Entry-level AI / ML Enthusiasts
  
• Career Switchers into AI & Data roles