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Industry-ready AI training with hands-on projects using Python, NumPy, Pandas, scikit-learn, TensorFlow and PyTorch. Learn NLP, computer vision, deep learning, model evaluation, explainability, deployment and MLOps. Build a strong AI portfolio and receive placement support for Data Scientist, ML Engineer and AI Research roles.
CDPL's Artificial Intelligence program covers fundamentals of AI and ML, Python for data science, supervised and unsupervised learning, deep learning with TensorFlow and PyTorch, NLP and computer vision, model evaluation and explainability, model deployment, MLOps, and ethical AI practices. The curriculum is designed for beginners and working professionals aiming for Data Scientist, ML Engineer, and AI Research roles.
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Learn practical AI and machine learning skills — from deep learning and NLP to MLOps and ethical AI — designed to help you ship real-world models and products.
Master deep learning architectures (CNNs, RNNs, transformers) and practical techniques for training production-grade neural networks for vision, language and time-series tasks.
Build robust ML pipelines: feature engineering, model selection, evaluation, hyperparameter tuning and deployment best practices for reliable, scalable AI systems.
Learn end-to-end data science workflows — data cleaning, exploratory analysis, statistical inference and storytelling with data to drive AI product decisions.
Hands-on NLP with transformers, sequence models, fine-tuning large language models, embeddings and retrieval-augmented generation for search, chatbots and summarization.
Implement modern computer vision solutions: image classification, object detection, segmentation, and practical approaches for deploying visual AI in real-world applications.
Explore generative models, diffusion models, fine-tuning strategies and creative AI workflows to build text, image and multimodal generation products.
Operationalize models with CI/CD for ML, monitoring, model versioning, reproducible training, and scalable serving to keep AI systems healthy in production.
Design and deploy AI responsibly by learning fairness, interpretability, privacy-preserving techniques and governance practices for trustworthy AI systems.
Translate business goals into AI success metrics — define KPIs, run experiments, measure impact, and iterate product features driven by data and user feedback.
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Become an AI Expert in Mumbai. Master the fundamentals of AI, deep learning, NLP, and intelligent automation systems with hands-on projects and industry certifications.
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Module 1-4: Introduction to AI, AI Ecosystem & Machine Learning Foundations, Introduction to Generative AI, Generative Learning & Technical Concepts. Building the base understanding of AI evolution, ML basics, and core Generative AI principles.
Module 5-7: The Evolution & Power of Large Language Models, Computer Vision & LLMs, Video, Speech & Generative AI Tools. Deep dive into LLMs, multimodal capabilities, and hands-on with tools like image generation, speech synthesis, and video AI.
Module 8: Prompt Engineering & Practical Applications. Advanced techniques including prompt design, contextual structuring, Chain-of-Thought, Few-Shot/Zero-Shot, ReAct, Tree-of-Thoughts, role-playing, structured outputs, function calling, and real-world prompt optimization.
Module 9-10: Responsible AI & Governance, ethical considerations, bias mitigation, prompt security, followed by Capstone Project & Certification. Apply all skills in end-to-end generative AI workflow.
Join 3,200+ AI practitioners who advanced their careers with our practical, industry-driven Artificial Intelligence & Machine Learning training. Learn MLOps, deep learning, large language models, and real-world deployment — designed to get you hired at top AI teams.
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2025-06-27 • Google
VerifiedI had the opportunity to intern at Cinute, and it has been a great learning experience... I worked on data analysis in Excel, created dashboards, and explored Power BI & Tableau. The quality of teaching is so good...
2025-06-27 • Google
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2025-06-27 • Google
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2025-06-27 • Google
VerifiedThe subjects taught are relevant and help prepare students for real-world challenges.
2025-06-27 • Google
VerifiedThe subjects taught are relevant and help prepare students for real-world challenges.
2025-06-27 • Google
VerifiedIt's a good opportunity to do course and learn coding languages... good mentors.
2025-06-27 • Google
VerifiedHelped me to learn and gain a lot of knowledge and skills growth throughout, humble and good communicating staff and members.
2025-06-27 • Google
VerifiedGood information provided by the domain providers, very good at communicating and humble...
2025-06-27 • Google
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2025-06-27 • Google
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Predict equipment failure using time-series data and deep learning.
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Identify and predict customers likely to leave a telecom company.
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Develop a deep learning model for image classification.
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Use time-series models to predict future stock prices.
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Work on projects based on real business scenarios from Fortune 500 companies across multiple industries.
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