| S.No |
Topic |
Sub-Topics |
| 1 | AI Frameworks | Definition, Types, Importance, Applications, Industry trends |
| 2 | TensorFlow Overview | Installation, Architecture, Graphs & Sessions, Tensors, Use cases |
| 3 | TensorFlow Basics | Constants & Variables, Operations, Data pipelines, Gradient computation, Optimizers |
| 4 | PyTorch Overview | Installation, Tensors, Autograd, Modules, Applications |
| 5 | PyTorch Basics | Tensor operations, Neural networks, Loss functions, Optimizers, Training loop |
| 6 | Keras Overview | Installation, Sequential & Functional API, Layers, Optimizers, Callbacks |
| 7 | Keras Model Building | Sequential model, Functional API, Model compilation, Training, Evaluation |
| 8 | Scikit-learn Overview | Installation, Preprocessing, Supervised learning, Unsupervised learning, Evaluation metrics |
| 9 | Scikit-learn Model Building | Classification, Regression, Clustering, Feature selection, Hyperparameter tuning |
| 10 | Caffe Framework | Installation, Architecture, Layers, Model training, Deployment |
| 11 | MXNet Framework | Installation, NDArray, Symbolic API, Gluon API, Deployment |
| 12 | Theano Framework | Installation, Symbolic computation, Tensors, Optimizations, Limitations |
| 13 | ONNX Framework | Overview, Model interoperability, Export & Import, Integration, Applications |
| 14 | Hugging Face Transformers | Installation, Pretrained models, Tokenizers, Fine-tuning, Applications |
| 15 | Fastai Framework | Installation, Data blocks, Model creation, Training, Transfer learning |
| 16 | OpenCV for AI | Installation, Image processing, Video processing, Computer vision models, Integration |
| 17 | DeepSpeech Framework | Installation, Speech recognition, Training models, Inference, Applications |
| 18 | Reinforcement Learning Frameworks | OpenAI Gym, Stable Baselines, RLlib, Training agents, Use cases |
| 19 | Explainable AI (XAI) Frameworks | LIME, SHAP, InterpretML, Use cases, Integration |
| 20 | AutoML Frameworks | TPOT, AutoKeras, H2O.ai, Features, Model selection |
| 21 | MLflow Framework | Experiment tracking, Model registry, Deployment, Integration, Use cases |
| 22 | Ray & Ray Tune | Installation, Distributed computing, Hyperparameter tuning, Integration, Examples |
| 23 | AI Frameworks for NLP | Transformers, SpaCy, NLTK, Gensim, Hugging Face |
| 24 | AI Frameworks for Computer Vision | OpenCV, TensorFlow CV, PyTorch CV, Detectron2, YOLO |
| 25 | AI Frameworks for Reinforcement Learning | OpenAI Gym, Stable Baselines, RLlib, Dopamine, Unity ML-Agents |
| 26 | AI Frameworks for Speech Recognition | DeepSpeech, SpeechBrain, wav2vec, ESPnet, Integration |
| 27 | Deployment of AI Models | TensorFlow Serving, TorchServe, ONNX Runtime, Flask API, Cloud deployment |
| 28 | Performance Optimization | GPU/TPU usage, Mixed precision, Quantization, Pruning, Profiling |
| 29 | Integration with Cloud Platforms | AWS Sagemaker, GCP AI Platform, Azure ML, Deployment, Monitoring |
| 30 | Future Trends in AI Frameworks | Multimodal models, AutoML, Distributed AI, Edge AI, Research directions |
