| 1 - About your certificate.html | 921.6 B | ||
| 1 - Bonus lecture.html | 9.1 KB | ||
| 1 - Configuring the Python Environment.mp4 | 21.2 MB | ||
| 1 - Crafting Effective Prompts Be Detailed and Specific.mp4 | 20.9 MB | ||
| 1 - Downloading and Installing Ollama Setup.mp4 | 14.7 MB | ||
| 1 - Introduction to Streamlit.mp4 | 34.6 MB | ||
| 1 - Introduction.mp4 | 63.9 MB | ||
| 1 - Model Compilation – Concepts and Process.mp4 | 43.6 MB | ||
| 1 - Overview to Memory in LangChain.mp4 | 28.4 MB | ||
| 1 - Overview of LangSmith and Its Capabilities.mp4 | 19.4 MB | ||
| 1 - Overview of Tools and Agents in LangChain.mp4 | 29.6 MB | ||
| 1 - Retrieval Augmented Generation Concepts.mp4 | 47 MB | ||
| 1 - Running Model Inference on Device.mp4 | 63.2 MB | ||
| 1 - Strengths and Limitations of Generative AI - foundation of AI.pdf | 3.2 MB | ||
| 1 - Strengths and Limitations of Generative AI.mp4 | 75 MB | ||
| 1 - Three Methods to Evaluate Prompt Quality.mp4 | 42.2 MB | ||
| 1 - Understanding LangChain Objectives and Core Benefits.mp4 | 25.5 MB | ||
| 1 - Understanding On-Device Model Deployment Steps.mp4 | 31 MB | ||
| 1 - Understanding Prompt Hyperparameters.mp4 | 39.5 MB | ||
| 1 - Using the Pipe Operator in LCEL.mp4 | 47.6 MB | ||
| 1 - What is On-Device AI.mp4 | 22.5 MB | ||
| 10 - Thought structures Skeleton-of-Thought Prompting.mp4 | 24.8 MB | ||
| 11 - Thought structures Program-of-Thought Prompting.mp4 | 32.9 MB | ||
| 2 - Best Practices for Prompting.mp4 | 35.2 MB | ||
| 2 - Bonus lecture.html | 9.1 KB | ||
| 2 - Building a GUI for Your GenAI App Using Streamlit.mp4 | 50 MB | ||
| 2 - Conducting Prompt AB Testing.mp4 | 21.4 MB | ||
| 2 - Configuring Ollama and downloading models.mp4 | 42.4 MB | ||
| 2 - Developing Custom Tools with LangChain.mp4 | 73.6 MB | ||
| 2 - Exploring the Qualcomm AI Hub.mp4 | 42.5 MB | ||
| 2 - Exporting and Downloading Your Model.mp4 | 70.5 MB | ||
| 2 - Generative AI The Magic Behind the Mechanism.mp4 | 71.3 MB | ||
| 2 - Hands-On Model Compilation.mp4 | 30.1 MB | ||
| 2 - LangChain Fundamentals Prompt Templates and LLM Models.mp4 | 28.9 MB | ||
| 2 - Model Training Phase – Concepts & Workflow.mp4 | 35.3 MB | ||
| 2 - Running and Monitoring Applications Using LangSmith.mp4 | 65.3 MB | ||
| 2 - Step 1 Reading Documents in RAG Workflow.mp4 | 82.3 MB | ||
| 2 - Temperature & Top-p Controlling Randomness.mp4 | 61.5 MB | ||
| 2 - Understanding Conversation Buffer Memory.mp4 | 66.4 MB | ||
| 2 - Understanding Runnables Theoretical Foundations.mp4 | 20.3 MB | ||
| 2 - Working with the Ollama Library in Python.mp4 | 56.1 MB | ||
| 3 - Customizing Memory Using Memory Keys and Adding Messages.mp4 | 30 MB | ||
| 3 - Evaluating Prompts with PromptFoo - Link to download nodejs.url | 102.4 B | ||
| 3 - Evaluating Prompts with PromptFoo - Prompts+and+test+cases+for+promptfoo.docx | 13.9 KB | ||
| 3 - Evaluating Prompts with PromptFoo.mp4 | 136.6 MB | ||
| 3 - Hands-On Model Training in Practice.mp4 | 32.3 MB | ||
| 3 - Invoking the Model via the Ollama REST API.mp4 | 23.7 MB | ||
| 3 - LangChain Built-in Tools DuckDuckGo Search and Wikipedia.mp4 | 70.2 MB | ||
| 3 - LangChain Fundamentals Formatting the Output.mp4 | 39 MB | ||
| 3 - Max Tokens & Stop Sequences Managing Output Length.mp4 | 23 MB | ||
| 3 - Model Profiling – Theory & Performance Insights.mp4 | 17.6 MB | ||
| 3 - Model customization via Command Line or Terminal.mp4 | 47.3 MB | ||
| 3 - Overview to Quantization.mp4 | 25.5 MB | ||
| 3 - Runnable Types Parallel, Passthrough, and Lambda.mp4 | 25.3 MB | ||
| 3 - Setting Up and Logging Into Qualcomm AI Hub.mp4 | 17.1 MB | ||
| 3 - Step 2 Creating Chunks in the RAG Process.mp4 | 65.2 MB | ||
| 3 - Understanding How AI Learns.mp4 | 92.8 MB | ||
| 3 - Using Prompt Templates for Consistency.mp4 | 32 MB | ||
| 3 -Link to download nodejs.url | 102.4 B | ||
| 4 - Building, Saving, and Implementing a Custom Ollama Model.mp4 | 33.3 MB | ||
| 4 - Evolution from Linear Regression to Neural Networks.mp4 | 77.8 MB | ||
| 4 - Example Managing Execution Flow with LCEL.mp4 | 90.5 MB | ||
| 4 - Implementing Conversation Chains.mp4 | 26.7 MB | ||
| 4 - Practical Model Profiling Exercise.mp4 | 65.2 MB | ||
| 4 - Presence & Frequency Penalties Adding Variety.mp4 | 15.7 MB | ||
| 4 - Prompting Framework Chain of Thought.mp4 | 114.7 MB | ||
| 4 - Step 3 Generating Embeddings in the RAG Workflow.mp4 | 40 MB | ||
| 4 - Symmetric Quantization Explained.mp4 | 42.8 MB | ||
| 4 - Working with Agents in LangChain.mp4 | 79.1 MB | ||
| 5 - Asymmetric Quantization Explained.mp4 | 52.5 MB | ||
| 5 - Building a Memory-Enabled Agent in LangChain.mp4 | 44.5 MB | ||
| 5 - Prompting Framework Step-Back Reasoning.mp4 | 29.5 MB | ||
| 5 - Step 4 Storing Embeddings in a Vector Database.mp4 | 60.8 MB | ||
| 5 - Tuning Prompt Parameters for Optimal Results - Prompt+parameter+tuning.ipynb | 10.9 KB | ||
| 5 - Tuning Prompt Parameters for Optimal Results.mp4 | 82.8 MB | ||
| 5 - Understanding Dynamic Routing in LangChain.mp4 | 21.3 MB | ||
| 5 - Understanding Tokens and Embeddings.mp4 | 61.7 MB | ||
| 5 - Working with Conversation Buffer Window Memory.mp4 | 25.9 MB | ||
| 6 - Applying Quantization Techniques – Hands-On.mp4 | 69.1 MB | ||
| 6 - Building an End-to-End RAG Application.mp4 | 73.6 MB | ||
| 6 - Implementing Dynamic Routing in LCEL.mp4 | 76.4 MB | ||
| 6 - Inside Transformers — The Core Architecture of LLMs.mp4 | 34.5 MB | ||
| 6 - Prompting Framework Role Prompting.mp4 | 21 MB | ||
| 6 - Understanding Conversation Summary Memory.mp4 | 30.9 MB | ||
| 7 - How Language Models Generate Predictions.mp4 | 47.4 MB | ||
| 7 - Prompting Framework Self-Consistency.mp4 | 26.5 MB | ||
| 7 - Using Runnables with Message History.mp4 | 40.3 MB | ||
| 8 - Pre-Training vs Fine-Tuning — How Models Evolve.mp4 | 51.6 MB | ||
| 8 - Prompting Framework Chain-of-Density.mp4 | 53.9 MB | ||
| 9 - Exploring Open-Source LLMs.mp4 | 18.6 MB | ||
| 9 - Thought structure Tree-of-Thought Prompting.mp4 | 102.1 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 93 total files | |||
Generative AI Skillpath: Zero to Hero in Generative AI
https://WebToolTip.com
Published 10/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 10h 15m | Size: 3.78 GB
Complete course on Generative AI: Prompting Engineering, Running LLMs locally (Ollama), Building AI apps using LangChain
What you'll learn
Design and engineer effective prompts using proven frameworks like Chain-of-Thought, Step-Back, and Role prompting.
Tune and control LLM behavior by adjusting hyperparameters such as temperature, top-p, max tokens, and penalties.
Run and customize Large Language Models locally using Ollama and integrate them with Python applications.
Build complete Generative AI workflows using LangChain, including prompt templates, chains, memory, and dynamic routing.
Develop Retrieval-Augmented Generation (RAG) systems that combine LLMs with vector databases for grounded, factual answers.
Design user-friendly AI interfaces using Streamlit and explore On-Device AI deployment with Qualcomm AI Hub.
Requirements
No prior AI or coding experience required—just a curious mindset, basic computer skills, and a PC with internet access.
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 2.5 GB | freecoursewb | 6 days | 20 | 11 | |
| 776.8 MB | freecoursewb | 6 days | 1 | 11 | |
| 2 GB | freecoursewb | 2 weeks | 27 | 34 | |
| 1.9 GB | freecoursewb | 1 month | 6 | 3 | |
| 1.1 GB | freecoursewb | 1 month | 42 | 30 |
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