Summarize Your Private Data with LLMs & Generative AI
Learn how to use generative AI (LLMs) to help you understand and generate the most important information from a large corpus of text. This could be used to help summarize a large document, or to help you find specifically what you want from large corpus of text (e.g. "How much did Company X charge us in Q2 for job Y?"). In this Guided Project we will create a chatbot that allows you to upload a PDF file, then subsequently ask questions to the chatbot about the contents of the PDF.
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Language
- English
Topic
- Artificial Intelligence
Enrollment Count
- 414
Skills You Will Learn
- Artificial Intelligence, Generative AI, watsonx, LLM
Offered By
- IBMSkillsNetwork
Estimated Effort
- 1 hour
Platform
- SkillsNetwork
Last Update
- May 9, 2025
A Look at the Project Ahead
- Grasp the Basics of Generative AI: Delve deep into how LLMs work, their underlying principles, and why they're transformative in information extraction and generation.
- Learn Automated Document Summarization: Equip yourself with the skills to generate concise summaries from extensive documents, retaining only the essential information, all with the help of LLMs.
- Harness the Power of llama2: Understand the basic of the llama2 LLM and how it can be used with vector store databases and the langchain framework to extract specific data points from large texts, be it business documents, academic papers, or any other vast corpus.
What You'll Need

Language
- English
Topic
- Artificial Intelligence
Enrollment Count
- 414
Skills You Will Learn
- Artificial Intelligence, Generative AI, watsonx, LLM
Offered By
- IBMSkillsNetwork
Estimated Effort
- 1 hour
Platform
- SkillsNetwork
Last Update
- May 9, 2025
Instructors
Bradley Steinfeld
Lover of technology and learning
I work for IBM. I like all tech, especially AI!
Read moreVicky Kuo
Data Scientist
I believe that success isn't just about individual milestones, but also about uplifting and encouraging others to reach their potential. This is why I'm passionate about combining my technical background with my eagerness to help people overcome technological hurdles and accelerate growth. When I’m not on the job, I love hiking with my two dogs or relaxing in a coffee shop. There's nothing better than having an insightful conversation over coffee, or even better, some volunteer work! Please feel free to reach out to me on LinkedIn.
Read moreSina Nazeri
Data Scientist at IBM
I am grateful to have had the opportunity to work as a Research Associate, Ph.D., and IBM Data Scientist. Through my work, I have gained experience in unraveling complex data structures to extract insights and provide valuable guidance.
Read moreContributors
Roodra Kanwar
Data Scientist at IBM
I am a data scientist by day, superhero by night. Psych! I wish I was that cool. Only the former part is true which is still pretty cool! I believe in constant learning and it is an essential part of being a productive data enthusiast. I am also pursuing my masters in computer science from Simon Fraser University specializing in Big Data. Moreover, knowledge is transfer learning (pun intended!) and what I have gained, I plan on reflecting it back to the data community.
Read moreFaranak Heidari
Data Scientist at IBM
Detail-oriented data scientist and engineer, with a strong background in GenAI, applied machine learning and data analytics. Experienced in managing complex data to establish business insights and foster data-driven decision-making in complex settings such as healthcare. I implemented LLM, time-series forecasting models and scalable ML pipelines. Enthusiastic about leveraging my skills and passion for technology to drive innovative machine learning solutions in challenging contexts, I enjoy collaborating with multidisciplinary teams to integrate AI into their workflows and sharing my knowledge.
Read more