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Advanced AI Development training course

This course covers advanced topics like fine-tuning GPT and AUTO-GPT models, understanding transformer architecture, using Langchain and Pandas for complex tasks, and exploring the latest research in the field.

JBI training course London UK

"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"

Brian Leek, Data Analyst, May 2022

Public Courses

04/11/24 - 2 days
£2500 +VAT
16/12/24 - 2 days
£2500 +VAT
27/01/25 - 2 days
£2500 +VAT

Customised Courses

* Train a team
* Tailor content
* Flex dates
From £1200 / day
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JBI training course London UK

Advanced AI Development Training: 

  • Review of AI Development Basics
  • Explore Advanced Topics in AI Development
  • Learn Advanced AUTO-GPT Applications
  • Learn Advanced Prompt Engineering  
  • Implement Vector Databases in AI Development
  • AI Ethics and Fairness
  • AI System Design and Architecture
  • Deploying and Maintaining AI Applications

 Unit 1: Review of AI Development Basics

  • 1.1 Recap of fundamental AI, Machine Learning and Deep Learning concepts
  • 1.2 Review of GPT and AUTO-GPT models
  • 1.3 Overview of AI development tools and libraries

Unit 2: Advanced Topics in AI Development

  • 2.1 Hyperparameter tuning in Machine Learning and Deep Learning
  • 2.2 Advanced techniques in feature engineering and data augmentation
  • 2.3 Deep dive into transformer models and advanced architectures
  • 2.4 Understanding Capsule Networks and Graph Neural Networks

Unit 3: Advanced AUTO-GPT Applications

  • 3.1 Building complex applications with AUTO-GPT
  • 3.2 AUTO-GPT in multi-turn conversations and dialog systems
  • 3.3 AUTO-GPT in advanced NLP tasks: summarization, translation, sentiment analysis
  • 3.4 Troubleshooting and optimizing AUTO-GPT applications

Unit 4: Advanced Prompt Engineering

  • 4.1 Advanced techniques for effective prompt design
  • 4.2 Prompt engineering for advanced tasks and complex domains
  • 4.3 Handling biases and ethical issues in advanced prompt engineering

Unit 5: Vector Databases in AI Development

  • 5.1 Deep dive into vector databases
  • 5.2 Use-cases and applications of vector databases in AI
  • 5.3 Best practices when using vector databases

Unit 6: AI Ethics and Fairness

  • 6.1 Advanced topics in AI Ethics: interpretability, explainability, accountability
  • 6.2 Understanding and mitigating bias in advanced AI models
  • 6.3 The role of regulation in AI

Unit 7: AI System Design and Architecture

  • 7.1 Designing robust and scalable AI systems
  • 7.2 Advanced topics in AI system architecture
  • 7.3 Designing AI systems for security and privacy

Unit 8: Deploying and Maintaining AI Applications

  • 8.1 Advanced topics in AI application deployment
  • 8.2 Monitoring and maintaining AI systems in production
  • 8.3 Ensuring the reliability and robustness of AI applications
JBI training course London UK

This course is ideal for those who already have an established knowledge base in AI/ML and some hands-on experience building, training and deploying models.

Learners should be comfortable with coding in Python and using libraries like TensorFlow, PyTorch, HuggingFace etc.

 


5 star

4.8 out of 5 average

"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"

Brian Leek, Data Analyst, May 2022



“JBI  did a great job of customizing their syllabus to suit our business  needs and also bringing our team up to speed on the current best practices. Our teams varied widely in terms of experience and  the Instructor handled this particularly well - very impressive”

Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022

 

 

JBI training course London UK

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Embark on a journey of advanced AI mastery with our specialized course, "Advanced AI Development." This program is meticulously curated to elevate your understanding and proficiency in artificial intelligence. Here's a sneak peek into the comprehensive units:

In Unit 1, we revisit the basics, providing a thorough recap of fundamental AI concepts, a review of GPT and AUTO-GPT models, and an overview of essential AI development tools and libraries.

Unit 2 advances into intricate topics, including hyperparameter tuning, advanced techniques in feature engineering, and a deep exploration of transformer models, Capsule Networks, and Graph Neural Networks.

Unit 3 unfolds the power of AUTO-GPT in complex applications, guiding participants through building multi-turn conversations, dialog systems, and mastering advanced NLP tasks like summarization and sentiment analysis.

Unit 4 takes a deep dive into prompt engineering, exploring advanced techniques for effective design while addressing biases and ethical challenges in complex domains.

Venture into the world of Unit 5, where vector databases become your playground. Understand their applications and grasp best practices when integrating them into your AI development journey.

Unit 1: Review of AI Development Basics

Q1: What topics are covered in the review of AI development basics?

A1: This unit provides a recap of fundamental AI, Machine Learning, and Deep Learning concepts. It also includes a review of GPT and AUTO-GPT models, as well as an overview of AI development tools and libraries.

Unit 2: Advanced Topics in AI Development

Q2: What advanced topics are covered in AI development? A2:

This unit delves into hyperparameter tuning in Machine Learning and Deep Learning, advanced techniques in feature engineering and data augmentation, as well as a deep dive into transformer models and advanced architectures. It also covers topics such as Capsule Networks and Graph Neural Networks.

Unit 3: Advanced AUTO-GPT Applications

Q3: What applications are explored in the Advanced AUTO-GPT unit?

A3: This unit focuses on building complex applications with AUTO-GPT, including its use in multi-turn conversations and dialog systems, advanced NLP tasks such as summarization, translation, and sentiment analysis. It also covers troubleshooting and optimizing AUTO-GPT applications.

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