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AI is shaping the future—from chatbots to self-driving cars. Learn the foundations of AI and apply it to real-world scenarios.
What You’ll Learn
Modules
Programming Essentials – 18 Hours
- Fundamentals of Programming
- Introduction to Python Programming
- Python Data Types and Operators
- Conditional Statements and Loops in Python
- Python Functions
- Object-Oriented Programming Concepts with Python
- Threading
Applied Data Science with Python – 36 Hours
- Introduction to Data Science
- Essentials of Python Programming
- NumPy
- Linear Algebra
- Statistics Fundamentals
- Probability Distributions
- Advanced Statistics
- Working with pandas
- Data Analysis
- Data Wrangling
- Data Visualization
- End-to-End Statistics Applications in Python
Machine Learning using Python – 48 Hours
- Machine Learning
- Supervised Learning
- Regression and its Applications
- Classification and its Applications
- Unsupervised Learning
- Ensemble Learning
- Recommendation Systems
Deep Learning Specialization – 42 Hours
- Introduction to Deep Learning
- Artificial Neural Networks
- Deep Neural Networks
- TensorFlow
- Model Optimization and Performance Improvement
- Convolutional Neural Networks (CNNs)
- Transfer Learning
- Object Detection
- Recurrent Neural Networks (RNNs)
- Transformer Models for Natural Language Processing (NLP)
- Getting Started with Autoencoders
- PyTorch
Advanced Deep Learning and Computer Vision – 44 Hours
- Introduction to Computer Vision
- Image Formation and Processing
- CNN Architectures and Transfer Learning
- Object detection
- Image Segmentation
- Variational AutoEncoder
- Generating Images with Neural Style
- Working with Deep Generative Models
- Optical Character Recognition
- Distributed and Parallel Computing for Deep Learning Models
- Explainable AI(XAI)
- Deploying Deep Learning Models and Beyond
Natural Language Processing – 28 Hours
- Working with Text Corpus
- Natural Language Processing Introduction
- Processing Raw Text with NLTK
- Natural Language
- Corpus
- Finding Useful Information from Piles of Text
- Text Analytics
- Developing a Speech to Text Application Using Python
- Feature Extraction
- Machine Learning
- Python Toolkits
- Bagging
- Deep Learning
Reinforcement Learning – 28 Hours
- Reinforcement Learning using OpenAI Gym
- Building Blocks of Reinforcement Learning
- The Multi Armed Bandit
- The Contextual Bandit
- Dynamic Programming Prediction Control and Value Approximation
- Markov Decision Processes and Neural Networks
- Model Free Prediction and Control with Monte Carlo (MC)
- Model Free Prediction and Control with Temporal Difference (TD)
Essentials of Generative AI, Prompt Engineering & ChatGPT – 12 Hours
- Generative AI and its Landscape
- Explainable AI
- Conversational AI
- Prompt Engineering
- Designing and Generating Effective Prompts
- Large Language Models
- ChatGPT and its Applications
- Fine-tuning ChatGPT
- Ethical Considerations in Generative AI Models
- Responsible Data Usage and Privacy
- The Future of Generative AI
- AI Technologies for Innovation
Advanced Generative AI – 20 Hours
- Introduction to Generative AI Models
- Introduction to Large Language Models and LangChain
- Advanced Prompt Engineering Techniques
- LangChainfor LLM Application Development
- LLM Fine-Tuning and Customization
- Benchmark and Evaluation of LLM Capabilities
AI Portfolio Project
Benefits After Completing the Course
Who Should Join?
Course Format
Duration
1 Year
Mode
Online
Projects
9 real-world projects
Placement Assistance
Yes