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From neural network fundamentals to advanced architectures
2 Weeks • 10 Hours
3 Weeks • 15 Hours
4 Weeks • 20 Hours
4 Weeks • 20 Hours
3 Weeks • 15 Hours
2 Weeks • 10 Hours
Transform industries with intelligent systems
Object detection, image classification, facial recognition, medical imaging, autonomous vehicles.
Chatbots, sentiment analysis, machine translation, text summarization, question answering.
Stock prediction, demand forecasting, anomaly detection, sensor data analysis, energy load prediction.
Disease diagnosis, drug discovery, medical image analysis, patient monitoring, personalized treatment.
Learn modern deep learning architectures
Your path to becoming an AI expert
Master Python for ML, mathematical foundations, and neural network basics. Build your first ML models from scratch.
Dive into CNNs for computer vision and RNNs for NLP. Work with real-world datasets and implement advanced architectures.
Master Transformers, GANs, Reinforcement Learning, and Graph Neural Networks. Implement cutting-edge research papers.
Deploy models to production, learn MLOps, and specialize in your chosen domain. Build portfolio projects and prepare for interviews.
Work with real-world data used in research and industry
14 million images across 20,000 categories for large-scale visual recognition.
Massive text dataset for NLP tasks including language modeling and text generation.
Medical imaging datasets for disease detection and healthcare applications.
Autonomous driving dataset with stereo images, LiDAR, and GPS data.
Build portfolio-worthy projects during the course
Build a YOLO-based system that detects and classifies objects in real-time video streams with high accuracy.
Develop a CNN-based system that helps radiologists detect anomalies in X-ray and MRI scans.
Create an intelligent chatbot using Transformer architecture that maintains conversation context across multiple languages.
Industry-standard tools for AI development
Google's end-to-end platform for machine learning with comprehensive tools and libraries.
Facebook's research-focused framework with dynamic computation graphs and Pythonic design.
High-level neural networks API running on top of TensorFlow with user-friendly interface.
Platform for state-of-the-art NLP models with thousands of pre-trained models available.
Comprehensive tools for every stage of AI development
NumPy, Pandas, OpenCV, Pillow for data manipulation and preprocessing pipelines.
Matplotlib, Seaborn, Plotly, TensorBoard for model debugging and result visualization.
AWS SageMaker, Google Colab, Azure ML, Paperspace for scalable training and deployment.
MLflow, Kubeflow, DVC, Weights & Biases for experiment tracking and model management.
Choose the right tool for your AI projects
High-demand roles in the AI revolution
Design and implement neural network architectures
Build image and video analysis systems
Develop language understanding systems
Conduct cutting-edge AI research
What you need and what you'll achieve
Basic Python knowledge (we'll cover advanced Python for ML)
High school level linear algebra and calculus (refresher provided)
Basic understanding of machine learning concepts (optional)
Receive Deep Learning Engineer Professional certificate upon completion
Join our Advanced Deep Learning course and launch your career as an AI expert
14-day money-back guarantee • Job placement assistance • GPU Lab Access