14. Essential Python Libraries for GenAI Requests & Pandas/16. Time Series Data Manipulation in Pandas.mp424.7MB
15. Introduction to LLMs, APIs and GenAI Libraries/1. Section Overview.mp437.26MB
15. Introduction to LLMs, APIs and GenAI Libraries/2. Foundations of LLMs and GenAI.mp472.51MB
15. Introduction to LLMs, APIs and GenAI Libraries/3. Tokens, Context Windows and Cost.mp422.58MB
15. Introduction to LLMs, APIs and GenAI Libraries/4. Exploring LLM APIs AI as a Service.mp492.14MB
15. Introduction to LLMs, APIs and GenAI Libraries/5. OpenAI Playground, Google AI Studio, and Anthropic Workbench.mp445.11MB
15. Introduction to LLMs, APIs and GenAI Libraries/6. Challenges and Limitations of LLMs.mp436.67MB
15. Introduction to LLMs, APIs and GenAI Libraries/7. The State of AI Present and Future – The Good and the Bad.mp493.55MB
16. Diving into OpenAI API with Python/1. Authenticating to OpenAI using Python Dotenv.mp491.89MB
16. Diving into OpenAI API with Python/2. Chat Completions Endpoint.mp465.88MB
16. Diving into OpenAI API with Python/3. The Developer Message.mp445.14MB
16. Diving into OpenAI API with Python/4. Streaming API Responses.mp460.69MB
16. Diving into OpenAI API with Python/5. Using Local Base64 Images as Input.mp469.79MB
16. Diving into OpenAI API with Python/6. Using Online Images as Input.mp416.72MB
16. Diving into OpenAI API with Python/7. Chat Completions API Parameters Temperature and Seed.mp470.7MB
16. Diving into OpenAI API with Python/8. Chat Completions API Parameters top_p, max_tokens, frequency penalty.mp4111.56MB
16. Diving into OpenAI API with Python/9. AI That Thinks Diving into OpenAI’s Reasoning Models (o1 and o3).mp468.43MB
16. Diving into OpenAI API with Python/10. Best Practices for Prompting Reasoning Models.mp451.4MB
16. Diving into OpenAI API with Python/11. Transcriptions with Whisper.mp486.62MB
16. Diving into OpenAI API with Python/12. Translations with Whisper.mp431.61MB
16. Diving into OpenAI API with Python/13. Text-to-Speech (TTS) API.mp440.75MB
16. Diving into OpenAI API with Python/14. Generating Original Images Using DALL-E 3.mp4132.59MB
17. Prompt Engineering for GenAI/1. Introduction to Prompt Engineering.mp421.8MB
17. Prompt Engineering for GenAI/2. Tactic #1 Position Instructions Clearly Using Delimiters.mp434.56MB
17. Prompt Engineering for GenAI/3. Tactic #2 Provide Detailed Instructions for Context, Outcome, or Length.mp493.9MB
17. Prompt Engineering for GenAI/4. Tactic #3 Use the RTF (Role-Task-Format) Structure.mp482.21MB
17. Prompt Engineering for GenAI/5. Tactic #4 Apply Few-Shot Prompting.mp4101.86MB
17. Prompt Engineering for GenAI/6. Tactic #5 Specify Steps Required to Complete a Task.mp465.52MB
17. Prompt Engineering for GenAI/7. Tactic #6 Give Models Time to Think.mp426.99MB
17. Prompt Engineering for GenAI/8. Other Tactics and Principles for Better Prompting.mp465.91MB
17. Prompt Engineering for GenAI/9. Avoiding Hallucinations Techniques for Guarding Outputs.mp429.88MB
17. Prompt Engineering for GenAI/10. Summary of Prompt Engineering.mp49.79MB
18. Diving into Google’s Gemini/1. Setting Up the Python SDK and Authenticating for Gemini API.mp486.98MB
18. Diving into Google’s Gemini/2. Generating Text From Text Prompts.mp448.15MB
18. Diving into Google’s Gemini/3. Streaming Gemini Responses.mp432.72MB
18. Diving into Google’s Gemini/4. Generating Text From Images.mp459.93MB
18. Diving into Google’s Gemini/5. Gemini API Generation Parameters Controlling How the Model Generates Responses.mp467.12MB
18. Diving into Google’s Gemini/6. Gemini API Generation Parameters Explained.mp488.54MB
18. Diving into Google’s Gemini/7. Building Chat Conversations.mp486.91MB
18. Diving into Google’s Gemini/8. Project Building a Conversational Agent Using Gemini.mp454.69MB
18. Diving into Google’s Gemini/9. System Instructions.mp442.44MB
18. Diving into Google’s Gemini/10. The File API Prompting with Media Files.mp483.13MB
18. Diving into Google’s Gemini/11. Tokens in Gemini API.mp466.51MB
18. Diving into Google’s Gemini/12. The File API Prompting with Audio.mp443.25MB
19. Diving into LangChain with OpenAI and Gemini/1. LangChain Demo.mp479.62MB
19. Diving into LangChain with OpenAI and Gemini/2. Introduction to LangChain.mp416.11MB
19. Diving into LangChain with OpenAI and Gemini/3. Working with the OpenAI Models.mp478.01MB
19. Diving into LangChain with OpenAI and Gemini/4. Caching LLM Responses.mp421.94MB
19. Diving into LangChain with OpenAI and Gemini/5. LLM Streaming.mp415.98MB
19. Diving into LangChain with OpenAI and Gemini/6. Prompt Templates.mp429.61MB
19. Diving into LangChain with OpenAI and Gemini/7. ChatPrompt Templates.mp451.23MB
19. Diving into LangChain with OpenAI and Gemini/8. Understanding Chains.mp479.71MB
19. Diving into LangChain with OpenAI and Gemini/9. Installing the Python SDK and Authenticating to Gemini.mp422.85MB
19. Diving into LangChain with OpenAI and Gemini/10. Integrating Gemini with LangChain.mp454.69MB
19. Diving into LangChain with OpenAI and Gemini/11. Using a System Prompt and Enabling Streaming.mp459.06MB
19. Diving into LangChain with OpenAI and Gemini/12. Multimodal AI Using Images as Input.mp4110.99MB
19. Diving into LangChain with OpenAI and Gemini/13. LangChain Tools DuckDuckGo and Wikipedia.mp4118.88MB
19. Diving into LangChain with OpenAI and Gemini/14. Creating a ReAct Agent.mp4114.33MB
19. Diving into LangChain with OpenAI and Gemini/15. Testing the ReAct Agent.mp467.74MB
20. Diving into Embeddings/1. Intro to OpenAI's Text Embeddings.mp428.35MB
20. Diving into Embeddings/2. Generating Simple Embeddings.mp451.84MB
20. Diving into Embeddings/3. Embedding the Dataset for Similarity Searches.mp452.03MB
20. Diving into Embeddings/4. Estimating Embedding Costs With Tiktoken.mp421.29MB
20. Diving into Embeddings/5. Performing Semantic Searches.mp428.44MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/1. Project Introduction.mp451.17MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/2. Loading Your Custom (Private) PDF Documents.mp453.49MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/3. Loading Different Document Formats.mp456.22MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/4. Public and Private Service Loaders.mp454.14MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/5. Chunking Strategies and Splitting the Documents.mp460.05MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/6. Intro to Vector Stores and Authenticating to Pinecone.mp473.87MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/7. Working with Pinecone Indexes.mp450.81MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/8. Working with Vectors.mp461.95MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/9. Pinecone Namespaces.mp432MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/10. Embedding and Uploading to a Vector Database (Pinecone).mp4109.67MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/11. Asking and Getting Answers.mp4108.67MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/12. Using Chroma as a Vector DB.mp488.54MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/13. Adding Memory to the RAG System (Chat History).mp489.59MB
21. Project RAG - Q&A Application on Your Private Documents (Pinecone and Chroma)/14. Using a Custom Prompt.mp489.77MB
22. Diving into LangGraph/1. LangGraph Concepts and Core Components.mp431.72MB
22. Diving into LangGraph/2. Building a ChatBot.mp438.27MB
22. Diving into LangGraph/3. Visualizing the Graph.mp48.62MB
22. Diving into LangGraph/4. Running the ChatBot.mp47.97MB
22. Diving into LangGraph/5. Tavily AI.mp4101.37MB
22. Diving into LangGraph/6. Enhancing the ChatBot with Tools.mp497.9MB
22. Diving into LangGraph/7. Adding Memory to the ChatBot.mp484.43MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/1. Quick Note.mp425.06MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/2. The Big Picture.mp442.27MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/3. Extracting Data from ArXiv with Pandas.mp4150.37MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/4. Downloading Research Papers.mp453.28MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/5. Prepping Data Loading, Splitting, and Expanding.mp494.46MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/6. Building a Knowledge Base with RAG and Embeddings.mp454.65MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/7. Creating a Pinecone Index.mp476.9MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/8. Loading the Knowledge Base and Deploying to Pinecone.mp445.84MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/9. Building Custom Tools.mp412.83MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/10. Implementing the ArXiv Fetch Tool.mp481.48MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/11. Unlocking Web Search with Google SerpAPI.mp434.19MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/12. Building Google SerpAPI Tools.mp431.55MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/13. Crafting RAG Tools.mp449.37MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/14. Implementing the Final Answer Generation Tool.mp418.33MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/15. Initializing the Oracle LLM.mp474.18MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/16. Testing the Ecosystem.mp438.87MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/17. Building a Decision-Making Pipeline.mp490.13MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/18. Defining the Agent State.mp413.02MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/19. Defining the Graph for Decision-Making.mp460.31MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/20. Generating Reports.mp494.79MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/21. Building the Final Research Report.mp467.03MB
23. Project Research Agent with LangGraph, GPT-4o, RAG, Pinecone, ArXiv, SerpAPI/22. Wrapping Up.mp499.18MB