Artificial Intelligence (AI) for Professionals | Enablers

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Become an Artificial Intelligence Engineer

Sessions Venue
Online & On Campus Apply Now

Benefits to join Boot Camp

Comprehensive 3-Month Training Program

State-of-the-Art Lab Facilities

Practical Learning Approach

Dedicated Student Support

Career Advancement Opportunities

Business support for dedicated students

What you'll learn

The "AI for Robotics" course provides a strong foundation in artificial intelligence and its application in robotics, covering topics like machine learning and computer vision. Students gain hands-on experience with robot programming, sensors, and actuators, while exploring advanced topics like autonomous systems and ethical AI. The course culminates in a capstone project, allowing students to create a functional robotics application and hone their problem-solving skills.

At the end of this program, you will be able to:

  • Master AI Fundamentals: Gain a comprehensive understanding of AI, learning over 100 AI tools and their real-world applications.
  • Explore AI in Business & Creativity: Learn how AI impacts business growth, enhances customer experiences, and transforms creative fields.
  • Ethics & Decision-Making: Understand ethical considerations in AI, its role in decision-making, and its influence on task automation.
  • AI Tools & Performance: Discover the latest AI tools like ChatGPT, Google Bard, and OpenAI SORA, and learn to measure AI performance and ROI.
  • Advanced AI Techniques: Dive into language processing, prompting engineering, chained prompting, and AI’s role in academic research and innovation.

Module Breakdown

Now…here’s something SUPER EXCITING that we have to share with you…

This is a complete overview of the actions you will take while building your business with the Enablers.

  • Getting Started with Python: Setup & Introduction
  • Control Flow: Decisions and Loops
  • Essential Data Structures: Lists, Tuples, Sets, and Dictionaries
  • Functions & Best Practices
  • Modular Coding: Imports, Modules & Packages
  • File Handling with Python
  • Error Handling Like a Pro
  • Object-Oriented Programming: Classes & Objects
  • Rapid App Prototyping with Streamlit
  • Machine Learning Concepts: Regression to Classification
  • Deep Learning for Natural Language Processing (NLP)
  • Simple RNNs: How Sequence Prediction Works
  • Neural Network Project (ANN) Implementation
  • Hands-On Project: Deep Learning with RNN
  • LSTM Networks Explained Intuitively
  • Project: LSTM & GRU for Text Predictions
  • Bidirectional RNNs: Predict the Next Word
  • Encoder-Decoder Architecture: Translating Sequences
  • Attention Mechanisms: Focus Where It Matters
  • Transformers: The Power Behind ChatGPT
  • Introduction to Generative AI & LLMs
  • LangChain 101: The GenAI Orchestrator
  • Getting Started with LangChain & OpenAI
  • Exploring Core Modules & Architecture of LangChain
  • OpenAI, Ollama & Other LLM Providers
  • Hands-On: Your First LLM App with LangChain
  • Building Smart Chatbots with Memory
  • Conversational Q&A Bots with Context
  • Complete GenAI App with LangChain
  • RAG Project: Llama2 + GROQ API for Docs
  • PDF Chatbot with NLP Capabilities
  • Search Engine with LangChain Tools & Agents
  • SQL Database Chat Interface with LangChain
  • Text Summarization Made Easy
  • YouTube & Webpage Content Summarizer (AI Agent Project)
  • Google GenAI: Solving Math Word Problems
  • LangChain + Hugging Face Integration
  • RAG Pipeline with AstraDB
  • Multilingual Coding Assistant with CodeLlama
  • Deploying GenAI Apps with Streamlit & HuggingFace
  • Building GenAI on AWS
  • Intro to Nvidia NIM with LangChain
  • Multi-Agent Systems with CrewAI
  • Hybrid Search: Vector DB + Cypher Queries
  • Graph Databases 101 with Cypher Language
  • LangChain + GraphDB: Practical Implementation
  • Fine-Tuning LLMs: Concepts & Workflow
  • End-to-End Fine-Tuning with Lamini
  • Building Stateful, Multi-Actor AI with LangGraph
  • Setting Up a Flask Project for AI
  • Integrating LLMs & Models into Flask
  • Building REST APIs for AI Services
  • File Upload Handling in AI Apps
  • Deploying Flask Apps on Cloud
  • Advanced Flask + AI Use Cases

MOMENTS TO BE REMEMBERED