AI/ML engineering Career Jumpstart

Live Class 1: The AI Landscape & Your Career Path

Topics: Introduction to AI & Machine Learning | Use cases in modern tech: Chatbots, Streaming Services, Autonomous Vehicles | Exploring career paths: AI Developer, Machine Learning Researcher, Data Scientist, MLOps Engineer, NLP & Computer Vision Experts | AI Job Market Trends: Salaries, Demand, and Freelance Opportunities | Future AI Trends: Generative Models, GPT, LangChain & Multi-Agent Systems | Navigating the AI Career Path: Basics → ML Concepts → Deep Learning → AI Engineering in Practice | Why AI is the Career of the Future | Success stories & Q&A

Live Class 2: The AI Engineer’s Workbench (Python & Data)

Topics: Introduction to Python for Artificial Intelligence | Setting up Jupyter Notebooks & Google Colab for AI Projects | Core Python concepts: Variables, Loops, and Functions (beginner-friendly) | Exploring Numpy: Arrays, Vectors & Basic Mathematical Operations | Introduction to Pandas: Dataset Manipulation, Rows & Columns | Essential Data Cleaning: Missing Values and Type Handling | Data Visualization Basics with Matplotlib | Introduction to Version Control: Overview of Git & GitHub

Live Class 3: Predictive Modeling & Intelligence Workflows

Topics: Understanding Datasets: Features & Labels | ML Pipeline Overview: Data Collection, Model Building, Prediction | Types of Machine Learning: Supervised vs Unsupervised (beginner-friendly) | Evaluating Models: Accuracy Metrics & Confusion Matrix | How to Share Your Work: GitHub/Notebook Presentation | Final Recap, Q&A & What’s Next in Your AI Learning Journey

Project: Intelligent Customer Churn Predictor