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Conversational AI with LLM

Transform Business Communications with Conversational AI and LLM

Course details

This course is designed to provide participants with a comprehensive understanding of Conversational AI and its practical applications across diverse business domains. Participants will explore the principles, techniques, and best practices for harnessing the power of Large Language Models (LLMs) to build robust and effective conversational systems. Whether you’re a business professional, data scientist, or developer, this course equips you with the knowledge and skills needed to leverage LLMs for creating advanced conversational AI solutions tailored to your organization’s specific needs.

Please bring along:

  • 1x Laptop
  • Purchased ticket

Schedule

  • Large Language Models: Architecture, Transformer, and Key Concepts

    Day 1

  • Building Question-Answering Systems with Large Language Models

    Day 2

  • Text Generation with HuggingFace

    Day 3

Course Producer

Samuel Chan

Machine learning practitioner in the field of marketing automation, fraud detection, finance and e-commerce. Samuel is Indonesia’s top-ranked Stack Overflow user in R (top 5% worldwide), a certified professional (certificates from Microsoft, MongoDB, Stanford University, John Hopkins University), and an experienced consultant that has worked with several public-trading companies from his time staying in China, Japan and Singapore.

Between 2017 and 2018, Samuel has trained and consulted with more than 20 companies around Indonesia and a regular guest speaker/trainer in a number of universities in Singapore and Indonesia. He is also among the first recipients of Microsoft Professional Program Certificate in Data Science in Southeast Asia, having demonstrated proficiency in R, Python, Microsoft Azure, SQL / T-SQL, PowerBI and a list of other technologies.

3-Day Workshop Modules

Syllabus: Conversational AI with LLM

Module 1: LLM – Architecture, Transformer, and Key Concepts

  • Overview of Large Language Models and their Architecture
  • Understanding what is Transformer
  • Explanation of pre-training and fine-tuning of language models
  • Introduction to popular Large Language Models like GPT-3, GPT-2, and BERT
  • Understanding the capabilities and limitations of Large Language Models
  • Explanation of the LangChain concept
  • Setting the API key and .env

Module 2: Building Question-Answering Systems with Large Language Models

  • Introduction to Question-Answering System
  • Steps involved in connecting databases with LLM
  • Basics of building a Question-Answering System using LLM with a database
  • Demonstration of using OpenAI and LangChain to build a Question-Answering System
  • Using LangChain and OpenAI to build a Question-Answering System with text data
  • Steps involved in connecting CSV data with LLM
  • Demonstration of using LangChain and OpenAI to build a Question-Answering System with text data

Module 3: Text Generation with HuggingFace

  • Introduction to the Text Generation model in HuggingFace
  • Setting the .env token key
  • Applying HuggingFace’s Inference API to use LLM without OpenAI credits
  • Integrating HuggingFace’s Inference API into the previously built Question-Answering System
  • Demonstration of using HuggingFace’s Inference API to build a Question-Answering System

Program Receivables:

  • Cutting Edge Curriculum

    A hands-on coding bootcamp with the opportunity to work on real datasets donated by businesses and the public sector. Coursebooks (PDF/HTML files), data set for practice, reference notes, and working files (R Notebook or Jupyter Notebook) are accessible through our Learning Management System account.

  • Project-Oriented Learning

    Work with real-life cases and learn under the assistance of our qualified instructors throughout the 1-month course.

  • Certification of Completion

    Show current and prospective employers that you’ve completed the course with a signed certificate of completion.

  • Quality Learning Environment

    We pay meticulous attention to the logistical details of our workshops: quality audio and visual setups, comfortable sitting arrangements, small group size. Dinners are included for evening workshops.

  • Engaging Community

    Be a part of our data-passionate community with 5000+ members and 300+ alumni.

A STRUCTURED APPROACH TO LEARNING DATA SCIENCE

The Large Language Model Specialization is a 4-week intensive program meticulously crafted to fast-track students’ expertise in harnessing large-scale linguistic models and their real-world applications.

No prior knowledge of Python, NLP, or deep learning principles is required. The course follows a well-structured learning trajectory, emphasizing hands-on exercises. Group mentoring sessions, led by our seasoned instructors and teaching assistants, provide insights and clarification throughout the learning process. For those keen on delving deeper into AI or understanding foundational theories, our Advanced Neural Network and Generative AI Specialization offers a comprehensive next step.

Throughout this specialization, participants will undertake a series of projects, each exploring the vast capabilities of Large Language Models in different scenarios. On completion, our dedicated career support team and industry mentors will assist graduates in navigating their path towards influential roles in AI and language model-centric sectors in leading organizations.

Learn LLM by building:

Students work through tons of real-life examples using sample datasets donated by our team of mentors and corporate partners. We believe in a learn-by-building approach, and we employ instructors who are uncompromisingly passionate about your growth and education.

Part of Large Language Models Specialization

This course is part of the Algoritma Large Language Models Specialization. Participants are rewarded with a certificate of completion upon passing criteria.

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Get In Touch

PT. Algoritma Data Indonesia.
RDTX Square, 9th Floor. Setiabudi, DKI Jakarta 12930.
Office: 0816-692-471
Email: community@algorit.ma

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