Artificial Intelligence Course in Kolkata
Industry Curriculum & Syllabus Modules
Foundations of Artificial Intelligence
History of AI, agent architectures, search algorithms, state spaces, and knowledge representation.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
Mathematics for Deep Learning
Multivariate calculus, gradients, matrix decomposition, and probability theory.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
TensorFlow 2.x & PyTorch Core
Tensors, autograd, building custom layers, models, and training loops.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
Deep Neural Networks (DNN) Architecture
Overfitting prevention, dropout, batch normalization, and optimization algorithms (Adam, RMSprop).
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
Computer Vision with CNNs
Convolutional filters, pooling, image classification, transfer learning with ResNet and VGG.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
Object Detection & Segmentation
Bounding boxes, YOLO (You Only Look Once), and OpenCV real-time video processing.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
Sequential Data & Recurrent Networks (RNN)
Vanishing gradients, LSTMs, and GRUs for time-series and sequential data forecasting.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
Natural Language Processing (NLP)
Word embeddings (Word2Vec), sequence-to-sequence models, and attention mechanisms.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
Transformers & Modern LLM Architecture
Self-attention, Transformer encoders/decoders, BERT, GPT, and prompt engineering.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
Generative AI & Diffusion Models
Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Stable Diffusion.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
Building LLM Applications with LangChain
Retrieval-Augmented Generation (RAG), vector databases (Chroma/Pinecone), and AI agent workflows.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
AI Capstone Project & Corporate Placement Drive
Develop a custom domain AI chatbot or vision system, mock technical interviews, and placement drives.
- Hands-on practical code implementations
- Live scenario architecture & debugging
- Enterprise code review & optimization
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