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10 Courses
This course teaches applied machine learning using Python, covering data preprocessing, model building, evaluation, and deployment. You will work with libraries like scikit-learn, pandas, and NumPy on real-world datasets to build practical skills.
Master deep learning concepts and techniques using TensorFlow. This course covers convolutional and recurrent neural networks, LSTMs, and how to apply these models in real-world AI applications for image and text data.
Learn natural language processing with state-of-the-art transformer models such as BERT and GPT. This course covers tokenization, embeddings, attention mechanisms, and fine-tuning transformer models for various NLP tasks.
Explore how artificial intelligence can transform business strategies and operations. Learn about AI-driven automation, decision-making, predictive analytics, and integration in various industries to boost efficiency and growth.
Learn computer vision techniques and applications using OpenCV. Covers image processing, object detection, facial recognition, and video analysis with hands-on coding exercises.
Discover reinforcement learning fundamentals by building algorithms from scratch. Learn about agents, environments, rewards, and policy optimization through coding practical examples.
Learn how to deploy AI and ML models using FastAPI. Covers building REST APIs, containerization, cloud deployment, and scaling AI applications for production environments.
Explore generative AI techniques such as GANs and diffusion models. Learn how to create realistic images, videos, and audio using cutting-edge generative networks and frameworks.
Understand the art of prompt engineering to maximize AI language model outputs. Covers prompt design, optimization techniques, and real-world applications with examples.
Learn to build intelligent AI chatbots using the Rasa framework. Covers natural language understanding and dialogue management for conversational AI.