01. Foundations & Python
This module builds the rock-solid foundation essential for any
AI professional. We go beyond basic syntax to cover advanced
programming techniques and the core libraries used for data
handling, analysis, and statistical validation in AI.
What you'll master:
-
Solving problems with advanced
Python Data Structures
-
Data Manipulation and Analysis with NumPy & Pandas
-
Data Visualization with Matplotlib & Seaborn
-
Validating results with statistical methods like
Hypothesis Testing
02. Machine Learning In-Depth
Go deep into the world of predictive modeling. You'll learn to
implement classical algorithms from scratch and use
industry-standard libraries to build and tune models that
solve real-world business problems, preparing you for common
Machine Learning interview questions.
What you'll master:
-
Supervised Learning: Regression, Classification, and
Logistic Regression
-
Unsupervised Learning: Clustering & Dimensionality
Reduction
-
Model Evaluation Metrics & Hyperparameter Tuning
-
Building Production-Ready Models with Scikit-learn
03. Deep Learning & Neural Networks
Unlock the power of neural networks to work with complex,
unstructured data like images, text, and audio. This module
demystifies
Deep Learning, covering the architecture of modern models and giving you
hands-on experience with the most popular frameworks.
What you'll master:
-
Building an
Artificial Neural Network
with TensorFlow & PyTorch
-
Image Recognition using a
Convolutional Neural Network (CNN)
-
Sequence Analysis with Recurrent Neural Networks (RNNs)
-
Advanced Techniques like Transfer Learning & Fine-Tuning
04. The Generative AI Revolution
Step to the absolute cutting-edge of AI. This module explores
the paradigm shift brought by Large Language Models (LLMs) and
diffusion models. You'll learn to build powerful applications
that can generate human-like text, code, and images with our
comprehensive
Generative AI course
module.
What you'll master:
-
Understanding the Transformer Architecture
-
Advanced Prompt Engineering Techniques
-
Fine-tuning Pre-trained LLMs on Custom Datasets
-
Building Applications with OpenAI and Hugging Face APIs
05. MLOps & Deployment
A model has no value until it's in production. This crucial
module covers the engineering principles to deploy, monitor,
and scale models reliably. You'll learn the fundamentals of
System Design
for AI and prepare for real-world cloud environments.
What you'll master:
-
Containerizing applications with Docker
-
Deploying Models as REST APIs using Flask/FastAPI
-
Building Advanced AI Pipelines with LangChain
-
Cloud Deployment and solving common
AWS interview questions
06. Capstone Project
Synthesize all your knowledge into a single, high-impact
project that will be the centerpiece of your portfolio. You'll
work on a real-world problem, building and deploying a
complete AI solution from scratch, similar to industry-level
Data Science projects for 2025.
Project domains include:
-
E-commerce Recommendation Engines
-
Financial Services Fraud Detection
-
Natural Language Chatbots for Customer Service
-
Custom Generative AI Content Creation Tools
