Week - 1

Introduction to AI Engineering

1. What is AI Engineering?
2. AI vs. Machine Learning vs. Generative AI
3. AI in modern business and industry
4. Understanding LLMs and AI-powered applications
5. Development environment setup

Week - 2

Python for AI Engineering

1. Python fundamentals and syntax
2. Variables, data types, conditions, and loops
3. Functions, modules, and packages
4. File handling and error handling
5. Practical Python exercises

Week - 3

Object-Oriented Programming & APIs

1. Classes, objects, and inheritance
2. Writing reusable software components
3. JSON and HTTP fundamentals
4. Working with REST APIs
5. Introduction to Git and GitHub

Week - 4

Generative AI & Prompt Engineering

1. How LLMs work
2. OpenAI, Claude, and Gemini APIs
3. Prompt engineering techniques
4. Structured outputs and function calling
5. Building a simple AI assistant

Week - 5

Building AI Applications with Python

1. Calling AI APIs from Python
2. Managing API keys and environment variables
3. Chat completion and response handling
4. Streaming responses
5. Building a business chatbot

Week - 6

Backend Development with Django / FastAPI

1. Backend architecture for AI applications
2. Creating APIs with Django or FastAPI
3. Connecting frontend and backend
4. Authentication and request validation
5. Developing an AI service endpoint

Week - 7

Working with Business Data & Databases

1. SQL and database fundamentals
2. Connecting AI applications to databases
3. Data cleaning and preparation
4. Business data retrieval
5. Building an AI-powered data query system

Week - 8

RAG & Knowledge-Based AI

1. What is Retrieval-Augmented Generation?
2. Embeddings and vector databases
3. Document processing and chunking
4. Building a company knowledge assistant
5. Improving accuracy and reducing hallucinations

Week - 9

AI Agents & Business Automation

1. Introduction to AI agents
2. Tools, workflows, and function calling
3. Automating repetitive business tasks
4. Email, CRM, and workflow integrations
5. Building an AI-powered automation workflow

Week - 10

AI Solutions for Business Departments

1. AI for customer support
2. AI for sales and marketing
3. AI for HR and recruitment
4. AI for finance and reporting
5. Business use-case analysis and solution design

Week - 11

Deployment, Security & Optimization

1. Deploying AI applications
2. Environment configuration
3. API security and data privacy
4. Cost optimization and monitoring
5. Testing and improving AI responses

Week - 12

Final Business AI Project & Presentation

1. Project planning and implementation
2. Building a complete AI business solution
3. Testing and debugging
4. Project presentation and demonstration
5. Career guidance and next steps

Get the opportunity to gain 1 month of practical internship experience after successfully completing the course. During the internship, participants will get the opportunity to work on 3 real-life projects and gain hands-on industry experience :

1. Real-world AI Project Development
2. Business Problem Analysis & AI Solution Design
3. AI Automation & AI Agent Development
4. API Integration ও AI Application Development
5. RAG & Knowledge-Based AI-এর Practical Implementation
6. Teamwork, Communication & Corporate Work Environment
7. Debugging, Testing & Project Deployment
8. Professional Portfolio & Project Presentation
9. Real-World Project Experience for Freelancing & Remote Jobs