Course Overview

Python has become the universal language of Artificial Intelligence, powering the research papers coming out of DeepMind, OpenAI, and Google Brain, as well as the production systems running inside every major technology company. Its rich ecosystem — TensorFlow, PyTorch, Keras, Hugging Face Transformers, and OpenCV — means you can go from a research paper to working code in days, not months. CETPA Infotech's Artificial Intelligence with Python Training in Noida is designed to make you fluent in this ecosystem, giving you the skills to build, train, evaluate, and deploy AI models that solve tangible business problems.

The programme is structured to progressively deepen your AI expertise across three pillars: machine learning (classical algorithms and feature engineering), deep learning (neural architectures for vision, language, and sequential data), and AI application development (integrating trained models into APIs and pipelines that real users can interact with). Each pillar is taught with hands-on Python projects so that theoretical concepts are always anchored in code you can run and inspect.

Our deep-learning modules are particularly comprehensive, covering CNN architectures (VGG, ResNet, EfficientNet) for image tasks, transformer-based models (BERT, GPT-style) for text tasks, and LSTM/GRU networks for time-series prediction. Trainers also cover the rapidly growing field of generative AI — including image generation with stable diffusion and text generation with large language models — so that your skills are calibrated to where the industry is heading, not just where it has been. Placement outcomes for AI-with-Python graduates at CETPA have been exceptional, with average starting packages of ₹6–9 LPA for fresh graduates.

Course Curriculum

• Python Advanced: NumPy, Pandas, Scikit-Learn
• Machine Learning: Regression, Classification, Clustering
• TensorFlow & Keras: Building & Training Neural Networks
• PyTorch: Tensors, Autograd, Custom Datasets
• CNN Architectures: LeNet, VGG, ResNet, EfficientNet
• Transfer Learning & Fine-Tuning
• Object Detection: YOLO, SSD, Faster R-CNN
• NLP: Tokenisation, Word2Vec, GloVe, BERT
• Hugging Face Transformers Library
• Sequence Models: LSTM, GRU, Attention
• Generative AI: VAE, GANs, Diffusion Models Overview
• MLOps: Model Versioning, Experiment Tracking (MLflow)
• FastAPI for Serving AI Models
• Capstone: Production-Ready AI Application