Building Practical Skills in NLP and Generative AI
Course 1293
3 DAY COURSE
Course Outline
Welcome to the 3-day intensive course on Building Practical Skills in NLP and Generative AI! This course is designed to equip you with a deep understanding and practical skills in the latest developments in Natural Language Processing (NLP) and Generative AI technologies.
By exploring foundational principles, advanced techniques, and real-world applications, this course will enable you to navigate and harness the capabilities of state-of-the-art AI models.
Building Practical Skills in NLP and Generative AI Benefits
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This course will address the following pain points:
- Foundation Building: Gain a solid understanding of the core concepts behind Generative AI and NLP.
- Advanced Techniques: Learn about the latest advancements in AI technologies including Transformers, GPT, and BERT architectures.
- Hands-On Application: Participate in hands-on labs to apply concepts in real-world scenarios.
- Industry Insight: Understand the applications of these technologies across various industries.
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Training Prerequisites
- Basic knowledge of Python programming is required as labs and examples use Python.
- Familiarity with general machine learning concepts is recommended but not essential.
- No advanced mathematical or deep learning knowledge is required upfront.
Skills in NLP and Generative AI Training Outline
Day 1: Foundations of Generative AI and NLP Basics
Module 1: Introduction to Generative AI
- Overview of Generative AI and its evolution.
- Introduction to Large Language Models (LLMs).
Module 2: Core Concepts of NLP
- Understanding Tokens, Embeddings, and Transformers.
- Architectural insights into NLP systems.
Module 3: Practical Applications
- Exploration of real-world applications of LLMs in various sectors.
- Future visions in AI technologies.
Lab 1: Hands-On with LangChain and VectorDB
- Using LangChain tools and VectorDB for enhanced NLP workflows.
Day 2: Deep Dive into Prompt Engineering and Advanced NLP
Module 4: Prompt Engineering Essentials
- Fundamentals of crafting effective prompts for AI.
- Techniques for refining AI outputs and iterative prompt engineering.
Module 5: Advanced NLP Techniques
- In-depth exploration of Bag-of-Words, TF-IDF, and modern word embeddings.
- Utilizing Python for complex NLP tasks.
Lab 2: Building Advanced NLP Models
- Implementing practical NLP solutions using advanced techniques.
Module 6: Introduction to Sequential Models
- Deep dive into RNNs, LSTMs, and the use of attention mechanisms.
Lab 3: Implementing LSTM for Text Generation
- You'll get hands-on experience with LSTMs by using them to generate text.
Day 3: Exploring Advanced Architectures and Predictive Analytics
Module 7: Understanding Advanced Generative Models
- Overview of Seq2Seq, Autoencoders, and the innovation of attention in these models.
Lab 4: Implementing a Seq2Seq Model for Machine Translation
- In this lab, you will use a Seq2Seq model to build a simple machine translation system.
Module 8: Deep Learning Architectures
- Comparative analysis of GPT and BERT architectures.
- Understanding their applications and advancements.
Lab 5: Applying LLMs in Predictive Analytics
- Practical session on leveraging LLMs for data augmentation and analysis.
Module 9: Future of AI and Wrap-Up
- Discussions on the ethical implications and future trends in AI.
- Review of the course content and guidance for further learning.
Private Team Training
Interested in this course for your team? Please complete and submit the form below and we will contact you to discuss your needs and budget.
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