AI Developer Career Accelerator:

AI Developer Advanced Course-Hands-On, Project-Based Learning-(Track 2)

CDsuper

Number of lessons: 39
AI Developer Fundamentals – Prerequisite Course (Track 1)

CDsuper

Number of lessons: 37

Chapter 1 – Foundations of AI & Machine Learning
- Lesson 1.1 – Introduction to AI & Machine Learning
- Lesson 1.2 – Key AI Career Paths & Industry Demand
- Lesson 1.3 – History & Evolution of AI
- Lesson 1.4: Understanding Supervised vs. Unsupervised Learning
- Lesson 1.5 – Intro to Neural Networks & AI Model Training Basics
- Lesson 1.6 – AI Model Evaluation & Performance Metrics
Chapter 2 – Python for AI Development
- Lesson 2.2 – Python Control Flow: Loops & Conditionals
- Lesson 2.1 – Getting Started with Python (Syntax, Variables, Data Types)
- Lesson 2.2 – Python Control Flow: Loops & Conditionals
- Lesson 2.3 – Functions, Modularization & Object-Oriented Programming (OOP)
- Lesson 2.4 – Working with Lists, Dictionaries & Tuples in AI Development
- Lesson 2.5 – Debugging & Error Handling in Python
- Lesson 2.6 – Hands-On Project: AI-Powered Calculator for Statistical Analysis
Chapter 3 – Mathematics for AI
- Lesson 3.1 – Linear Algebra for AI (Vectors, Matrices, Eigenvalues)
- Lesson 3.2 – Probability & Statistics (Distributions, Bayes Theorem, Hypothesis Testing)
- Lesson 3.3 – Calculus in AI (Gradients, Derivatives, Optimization Techniques)
Chapter 4 – Data Science & Machine Learning Fundamentals
- Lesson 4.1 – Introduction to Data Preprocessing: Cleaning, Normalization & Feature Engineering
- Lesson 4.2 – Building a Simple Neural Network from Scratch
- Lesson 4.3 – Data Preprocessing & Cleaning Techniques
- Lesson 4.4 – Feature Engineering: Transforming Raw Data for ML Models
- Lesson 4.5 – Supervised Learning: Regression & Classification Models
- Lesson 4.6 – Unsupervised Learning: Clustering & Dimensionality Reduction
- Lesson 4.7 – Model Evaluation: Accuracy, Precision, Recall & F1 Score
- Lesson 4.8 – Hands-On Project: Predictive Model for Customer Behavior
Chapter 5 – AI Ethics & Responsible AI Development
- Lesson 5.1 – Bias & Fairness in AI Models
- Lesson 5.2 – Privacy & Security Concerns in AI Applications
- Lesson 5.3 – Regulatory Guidelines & Ethical AI Decision-Making
- Lesson 5.4 – Explainability & Transparency in AI Systems
- Lesson 5.5 – Hands-On Project: Detecting Bias in Datasets Using Python
Chapter 6 – Capstone & Final Work
- Lesson C1 – Capstone Project Design & Scoping
- Lesson C2 – Building an End-to-End ML Pipeline
- Lesson C3 – Model Comparison & Benchmarking
- Lesson C3 – Model Comparison & Benchmarking
- Lesson C4 – Responsible AI in Practice
- Lesson C5 – Capstone Presentation & Reporting
- Lesson C6 – Portfolio & Career Integration
- Lesson C7 – Course Wrap-Up & Certification

AI Developer Advanced Course-Hands-On, Project-Based Learning-(Track 2)

AI Developer Fundamentals – Prerequisite Course (Track 1)

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