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Generative AI For Beginners

GitHub, Prompt Engineering, RAG , Fine-tuning, AI Automation , Hugging Face,5+ Generative-AI Projects

     
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Generative AI For Beginners

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  • icon5 (1 reviews )
  • icon4.5 total hours
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About Generative AI For Beginners

Generative AI for Beginners: (Cover Langchain, Prompt Engineering ,Hugging Face, RAG , Fine Tunning to get you started in Generative AI in less than 5 hours).

(Basic's + Demo Use case for all)

Why Take This Course?

Artificial Intelligence is revolutionizing industries across the globe, creating unprecedented opportunities for innovation and growth. By diving into Generative AI, you're positioning yourself at the forefront of this technological revolution. Here's why this course is crucial for your career:

1. High Demand: AI engineers are among the most sought-after professionals in tech, with demand far outpacing supply.

2.Lucrative Career: Generative AI offers some of the highest salaries in the tech industry, reflecting the value and scarcity of these skills.

3. Innovation Driver: Gain the skills to create cutting-edge AI solutions that can solve real-world problems and transform industries.

4. Future-Proof Skills: AI is here to stay. These skills will remain relevant and valuable for decades to come.

5. Versatility: The knowledge gained is applicable across various sectors, from healthcare to finance, retail to robotics.

This course provides a comprehensive introduction to Generative AI, equipping you with practical, in-demand skills that will set you apart in the job market and open doors to exciting career opportunities.

Course Content

In this Generative AI for Beginners course, you will learn:

1. GitHub for Data Science: Version control and collaboration tools for managing data science projects.

2. CI for Data Science: Continuous Integration practices tailored for data science workflows.

3. Prompt Engineering: Techniques to effectively communicate with and guide AI models.

4. RAG (Retrieval-Augmented Generation): Methods to enhance AI responses with external knowledge.

5. Fine-tuning: Customizing pre-trained AI models for specific tasks or domains.

6. AI Automation: Streamlining AI processes and workflows for increased efficiency.

7. Hugging Face: Utilizing this popular platform for accessing and deploying AI models.

This is a short course with a perfect blend of theory + code.

One can take this course understanding everything and then choose the use case they want and dive deep.

What You Will Learn?

  • Introduction to AI/ML concepts and tools.
  • Building a ChatGPT clone using Google's Gemini model.
  • Using GitHub for data science and AI projects.
  • Implementing continuous integration for data science/AI workflows.
  • Prompt engineering techniques for better AI interactions.
  • Document search capabilities in AI systems.
  • Understanding and working with word embeddings.
  • Using Hugging Face tools and models.
  • AI automation techniques.
  • Retrieval-Augmented Generation (RAG) for enhancing AI responses.
  • Fine-tuning AI models for specific tasks.
  • Cover 5-6 AI projects.