Masters in Data Science with AI & ML
Become an expert in AI & Data Science — build intelligent systems, chatbots,and deploy them professionally.
Hands-on ML & AI program covering algorithms, neural networks, NLP, computer vision, and real-world projects. Learn to build and deploy intelligent systems and prepare for AI engineering careers.
Course overview
Hands-on ML & AI program covering algorithms, neural networks, NLP, computer vision, and real-world projects. Learn to build and deploy intelligent systems and prepare for AI engineering careers.
Technologies
Learning Outcomes
Learning roadmap
Six phases. Each one ends with a portfolio build you can demo.
Python Programming Foundations
Programming Concepts - Introduction to Programming - Python Installation & Environment Setup - Variables, Data Types, Operators - Input / Output Operations - Control Structures - Conditional Statements - Loops (for, while) - break, continue, pass - User-defined & Built-in Functions - Lists, Tuples, Sets - Dictionaries - Iteration Techniques - Modules & Packages - File Handling (CSV, TXT) - Exception Handling - Object-Oriented Programming (OOP) - Mini Project: simple calculator
Data Analysis, Excel,Statistics & Visualization
Types of Data (Qualitative, Quantitative) - Mean, Median, Mode - Variance, Standard Deviation - Probability & Correlation - Linear Algebra Basics: Arrays & Matrix Operations - Indexing & Slicing - Mathematical Functions - Series & DataFrames - Data Cleaning & Wrangling - Formulas & Functions - Pivot Tables - Charts & Dashboards - Tableau: Connecting to Data Sources - Visual Analytics - Dashboards & Storytelling - Matplotlib (Bar, Line, Histogram, Pie) - Seaborn (Heatmaps, Boxplots) - GroupBy & Aggregation - Missing Value Handling - Mini Project: Exploratory Data Analysis on Real-World Dataset
Machine Learning
ML Workflow - Types of Learning (Supervised, Unsupervised, Reinforcement) - Feature Selection - Train-Test Split - Model Evaluation Metrics - Linear Regression - Logistic Regression - K-Nearest Neighbors (KNN) - Decision Trees - Random Forest - Support Vector Machines (SVM) - Hyperparameter Tuning - K-Means Clustering - Hierarchical Clustering - Principal Component Analysis (PCA) - Mini Project:Customer Segmentation System
Deep Learning, NLP & Computer Vision
Neural Networks - Activation & Loss Functions - Backpropagation - Model Building & Training - Artificial Neural Networks (ANN) - Convolutional Neural Networks (CNN) - Recurrent Neural Networks (RNN) - Transfer Learning - Text Preprocessing - TF-IDF & Word Embeddings - Sentiment Analysis - Image Processing - Face Detection - Object Detection Basics - Mini Project:Face Recognition System
Advanced AI & Generative Models
Transformer Architecture - Pre-trained Models - Text Classification & Question Answering (QA) - YOLO Architecture - Custom Dataset Training - Real-Time Object Detection - LLaMA Overview - Prompt Engineering - LangChain (Chains, Agents, Memory) - OpenAI API - Gemini API - AI Chatbot Development - Mini Project: AI Chatbot using LangChain
R, SQL, Capstone & Career Preparation
Data Manipulation with dplyr - Data Visualization with ggplot2 - DBMS & RDBMS Concepts - MySQL / PostgreSQL - CRUD Operations - Joins & Subqueries - Mini Project:Sales Management Database
Meet Your mentors
Anexa Thomas
Data Science Trainer
Robin Shiji
Python Trainer
Ready to start Masters in Data Science with AI & ML?
Book a consultation — we'll map your background to the right cohort and schedule.