Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
5 Hour(s) 40 Minute(s)
Language
English
Taught by
Abdurrahman TEKIN
Rating
3 views
Course Overview
Hands-On Projects with Ollama, Langchain, CrewAI, and HuggingFace to Enhance Your AI Skills and Transform Everyday Tasks
Welcome!
This comprehensive course is designed for individuals eager to dive into the world of Large Language Models (LLMs) and harness their power to create innovative applications that can simplify tasks in everyday life.
Course Overview
In this course, you will learn how to effectively utilize various libraries and frameworks, including Ollama, LangChain, CrewAI, and Hugging Face, to build practical projects that demonstrate the capabilities of LLMs. Through hands-on projects, you will gain a deep understanding of how these technologies work together to enhance productivity and creativity.
What You Will Learn
Understanding LLMs: Gain insights into the architecture and functioning of Large Language Models, including their applications in natural language processing (NLP).
Ollama and LangChain: Learn how to leverage Ollama for efficient model deployment and LangChain for building complex applications that integrate multiple components seamlessly.
Hugging Face Transformers: Explore the Hugging Face library to access a wide range of pre-trained models for various NLP tasks.
Practical Applications: Implement real-world projects that showcase the power of LLMs in different contexts.
Project Highlights
Learning Python Tool with Ollama: Create an interactive tool that helps users learn Python programming through guided exercises and instant feedback using an LLM.
Make a Video Describer: Develop an application that generates descriptive text for video content, enhancing accessibility and understanding for users.
Chat with PDF using Ollama LLM: Build a chat interface that allows users to ask questions about the content of PDF documents, providing instant answers powered by an LLM.
Chat with VIDEO using Ollama LLM and Whisper: Combine video processing with speech recognition to create an application where users can interact with video content through natural language queries.
Get Model Answers Based on Long Stories: Design a system that allows users to input long narratives or stories and receive concise answers or summaries from the model.
Chat with Your Note: Create a personal note-taking application where users can interact with their notes using natural language queries, making information retrieval seamless.
Chat with Your Diary: Develop a diary application that allows users to reflect on their entries and ask questions about their past experiences, promoting self-reflection and personal growth.
Continuous Learning
This course is designed to be dynamic, with new projects added regularly to keep pace with advancements in technology and user needs. You will have the opportunity to explore new ideas and implement them in your projects, ensuring you stay ahead in the rapidly evolving field of AI and NLP.
Who Should Enroll
This course is ideal for:
Developers looking to expand their skill set in AI and machine learning.
Data scientists interested in applying NLP techniques using state-of-the-art models.
Anyone passionate about leveraging LLMs to create innovative applications that enhance productivity.
Join us on this exciting journey as we explore the potential of Large Language Models through practical projects. By the end of this course, you will have the skills and knowledge needed to build your own applications using Ollama, LangChain, CrewAI, and Hugging Face, empowering you to make your life easier through technology. Enroll today and start mastering LLMs!
Course Content
- 5 section(s)
- 37 lecture(s)
- Section 1 Introduction
- Section 2 Ollama
- Section 3 Langchain
- Section 4 CrewAI
- Section 5 HuggingFace
What You’ll Learn
- Understanding LLMs: Gain a solid foundation in Large Language Models (LLMs) and their applications.
- Using Ollama: Learn how to utilize the Ollama library for various NLP tasks.
- LangChain Integration: Master the integration of LangChain for building complex applications with LLMs.
- Project Development: Develop practical projects that reinforce learning.
- Creating a Learning Python Tool with Ollama.
- Building a Video Describer that summarizes video content.
- Implementing a Chat with PDF feature using Ollama LLM.
- Developing a Chat with VIDEO application using Ollama LLM and Whisper for audio transcription.
- Designing a system to Get Model Answers based on long stories or texts.
- Creating a Chat with Your Note application to interact with personal notes.
- Building a Chat with Your Diary project to reflect on personal experiences and insights.
- Whisper Integration: Understand how to integrate Whisper for audio processing and transcription tasks.
- Hugging Face Models: Learn how to leverage Hugging Face models for text generation and other NLP tasks.
- Practical Skills: Acquire hands-on experience through coding exercises and project implementations.
- Problem-Solving Techniques: Develop skills to tackle real-world problems using LLMs and related technologies.
- Additional Benefits: Continuous updates with new projects to enhance learning and keep up with advancements in AI and NLP technologies.
Skills covered in this course
Reviews
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MMARIUS CASTALIU
has some good content here and there, hard to follow the presenter's English language. jumping up and down in code while speaking English with an accent was getting hard to follow at some point.
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CCijo Vadakkethala
I would really like to appreciate for this training. Its very much understandable. Lots of variety in examples which is helpful. It will be better if you can explain or define certain terminologies for learners who are very new to such models.
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SStancho Stanchev
The corse is good. Explanations are going along the Python code, which really makes things much clear. Useful practical use cases are covered.
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FFERNANDA COLONEZI MILAGRES
The course provides a good overview and presents several small projects that offer ideas and help us practice. However, being more generic, it doesn't go into much depth so far, making it difficult to apply this knowledge to real-world problems that require adding context, fine-tuning, and using more robust production models. So, we won't achieve "mastery" yet, but it's interesting to have a general overview of various open-source tools and be able to quickly deploy prototypes.
