Hands-On AI: Build, Train, and Deploy Advanced AI Projects

Unlock AI Mastery: Practical Projects for ChatGPT, Anomaly Detection, Streamlit Chatbots, RAG and More


What you'll learn
Train Custom ChatGPT Models: Implement Reinforcement Learning from Human Feedback (RLHF) to create your own ChatGPT.
Master LLMs: Build and fine-tune Large Language Models using advanced techniques like RNNs, LSTMs, and Transformers.
Detect Anomalies Efficiently: Develop end-to-end anomaly detection systems using autoencoders.
Create Advanced Chatbots: Build interactive chatbots with Streamlit, integrating Langchain and GPT for sophisticated conversations.
Leverage RAG Techniques: Apply Retrieval-Augmented Generation (RAG) with Llama2 and the FAISS Vector Database.
Gain Real-World Coding Skills: Work on practical coding exercises that prepare you for real-world AI applications.
Optimize AI Models: Learn the full workflow from data preparation to model evaluation and optimization.
Join a Supportive Community: Access a community for collaboration, support, and enhancing your problem-solving skills.

Requirements
Basic Understanding of Python: Familiarity with Python programming, including basic syntax, data structures, and libraries.
Fundamental Knowledge of Machine Learning: Understanding of core machine learning concepts, such as supervised and unsupervised learning, regression, and classification.
Basic Understanding of Neural Networks: Awareness of neural network structures and basic concepts, including feedforward and backpropagation.
Access to a Computer: A computer with internet access to run coding exercises and use development environments.
Development Environment: Installation of Python and Jupyter Notebooks. Instructions will be provided if needed.

Description
Unlock the power of artificial intelligence with our comprehensive, project-based course designed for intermediate to advanced learners. Whether you’re looking to enhance your AI skills or gain hands-on experience with real-world projects, this course has everything you need to master AI applications.
What You'll Learn:
Project 1: Retrieval-Augmented Generation (RAG) with LLMs and FAISS
Learn RAG architecture fundamentals
Differentiate between LLM pretraining and fine-tuning
Implement Llama2 with the FAISS Vector Database
Detailed code walkthroughs and practical applications
Project 2: Train Your Own ChatGPT with RLHF
Understand Reinforcement Learning from Human Feedback (RLHF)
Deep dive into RLHF techniques
Implement RLHF on VertexAI
Evaluate and optimize your ChatGPT model
Project 3: Building and Fine-Tuning Large Language Models (LLMs)
Explore RNNs, LSTMs, and Attention mechanisms
Master Tokenizers and Encoder-Decoder architectures
Dive into Transformer models and their variations
Practical walkthroughs on prompt engineering
Project 4: Anomaly Detection Using Autoencoders
Develop an end-to-end anomaly detection system
Implement autoencoders for effective anomaly detection
Hands-on coding with provided datasets
Project 5: Build a Streamlit Chatbot Using Langchain and GPT
Create interactive chatbots with Streamlit
Integrate Langchain and GPT for advanced conversational AI
Step-by-step coding guidance and data handling
Course Features:
Hands-On Projects
: Real-world AI applications to solidify your learning
Expert Guidance
: Step-by-step instructions and deep dives into complex topics
Comprehensive Resources
: Code, data, and additional materials provided
Community Support
: Join our community for collaboration and problem-solving
Who This Course Is For:
AI enthusiasts with an intermediate understanding of AI and machine learning
Developers looking to build and deploy advanced AI applications
Professionals aiming to enhance their AI skill set with practical projects
Join us in this exciting journey to master AI through hands-on, real-world projects. Enroll now and start building the future of AI today!
Who this course is for:
AI Enthusiasts: Individuals passionate about artificial intelligence and looking to advance their understanding with real-world applications.
Intermediate to Advanced Learners: Those with a foundational knowledge of Python and machine learning who want to tackle more complex AI projects.
Developers and Engineers: Software developers and engineers aiming to enhance their AI skill set and apply it to real-world problems.
Data Scientists: Data scientists seeking to expand their toolkit with advanced AI techniques and applications.
Students and Academics: Learners in academic settings who want to complement their theoretical studies with practical experience.
Professionals Seeking Career Growth: Individuals in the tech industry looking to transition into AI roles or enhance their current positions with cutting-edge AI skills.
Entrepreneurs and Innovators: Those interested in leveraging AI to drive innovation in their startups or businesses.

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