Basics of ChatGPT Development and Automation

Course description

This is an introductory course on how to use ChatGPT as an assistant in tasks related to the development lifecycle of applications and automating time consuming tasks. It covers topics such as the recent evolution of Large Language Models, development and scripting use cases and the basics of prompt engineering.

Every student has assigned to him his own virtual lab environment setup.

Duration

This course takes place over 2 working days.

What will you learn

● Understand what ChatGPT is and its capabilities.
● Use ChatGPT to increase your productivity.
● Learn how to use ChatGPT to build scripts, generate documentation, generate unit tests.
● Learn how to use ChatGPT how to translate a code into human readable text.
● You will understand how ChatGPT can be used in order to debug code, detect bugs and be used for code completion.

Target audience

This course is suitable for:

• Developers, programmers, sys admins looking to incorporate ChatGPT into their projects.
• Developers, programmers who want to learn more about AI and natural language processing.
• professionals who want to learn how to use ChatGPT to improve their workflow and achieve more in less time.

Prerequisites:

The course is best attended with a general knowledge about programming, scripts and data formats.

Module 1: Intro to ChatGPT

  • Demo
  • The chat interface
  • Storing conversations

Module 2: Why was ChatGPT released now?

  • Introduction to Natural Language Processing
  • The road to Large Language Models: Transformers, BERT and GPT
  • From simple tasks to understanding instructions: GPT3 to InstructGPT
  • Understanding the size of ChatGPT

Hands-on Lab

Module 3: ChatGPT for scripts

  • Bash, Python and Perl scripts
  • Scripts for manipulating the file system
  • Scripts for automation
  • The problem with web scraping

Hands-on Lab

Module 4: ChatGPT for data format conversions

  • Writing proper queries for the task
  • JSON, YAML, CSV, SQL

Hands-on Lab

Module 5: ChatGPT for generating documentation

  • Commenting code
  • Generating standardized docs

Hands-on Lab

Module 6: ChatGPT for generating unit tests

  • Testing applications without the boilerplate

Hands-on Lab

Module 7: ChatGPT for explaining code

  • Why having a high-level summary of code helps
  • How much should you trust the explanations?

Hands-on Lab

Module 8: ChatGPT for detecting bugs

  • What types of bugs are easier to detect automatically?
  • Asking for help the right way

Hands-on Lab

Module 9: ChatGPT prompt engineering fundamentals

  • What is prompt engineering?
  • Why does ChatGPT understand some prompts better?
  • Tips and tricks for getting more consistent results

Hands-on Lab

Note:​​

Every student has assigned to him his own virtual lab environment setup.

Additional details:

To attend this course, you need to have:
• PC/Laptop with internet access
• Updated web browser

Basics of ChatGPT Development and Automation

Price On-Demand
  • DURATION: 2 days
  • SKILL LEVEL: Associate
  • LECTURES: 9 lessons

Register
  • PRICE: On-Demand
  • DURATION: 2 days
  • SKILL LEVEL: Associate
  • LECTURES: 9 lessons

Course description:

This is an introductory course on how to use ChatGPT as an assistant in tasks related to the development lifecycle of applications and automating time consuming tasks. It covers topics such as the recent evolution of Large Language Models, development and scripting use cases and the basics of prompt engineering.

Every student has assigned to him his own virtual lab environment setup.

Duration

This course takes place over 2 working days.

What will you learn

● Understand what ChatGPT is and its capabilities.
● Use ChatGPT to increase your productivity.
● Learn how to use ChatGPT to build scripts, generate documentation, generate unit tests.
● Learn how to use ChatGPT how to translate a code into human readable text.
● You will understand how ChatGPT can be used in order to debug code, detect bugs and be used for code completion.

Target audience

This course is suitable for:

• Developers, programmers, sys admins looking to incorporate ChatGPT into their projects.
• Developers, programmers who want to learn more about AI and natural language processing.
• professionals who want to learn how to use ChatGPT to improve their workflow and achieve more in less time.

Prerequisites:

The course is best attended with a general knowledge about programming, scripts and data formats.

Module 1: Intro to ChatGPT

  • Demo
  • The chat interface
  • Storing conversations

Module 2: Why was ChatGPT released now?

  • Introduction to Natural Language Processing
  • The road to Large Language Models: Transformers, BERT and GPT
  • From simple tasks to understanding instructions: GPT3 to InstructGPT
  • Understanding the size of ChatGPT

Hands-on Lab

Module 3: ChatGPT for scripts

  • Bash, Python and Perl scripts
  • Scripts for manipulating the file system
  • Scripts for automation
  • The problem with web scraping

Hands-on Lab

Module 4: ChatGPT for data format conversions

  • Writing proper queries for the task
  • JSON, YAML, CSV, SQL

Hands-on Lab

Module 5: ChatGPT for generating documentation

  • Commenting code
  • Generating standardized docs

Hands-on Lab

Module 6: ChatGPT for generating unit tests

  • Testing applications without the boilerplate

Hands-on Lab

Module 7: ChatGPT for explaining code

  • Why having a high-level summary of code helps
  • How much should you trust the explanations?

Hands-on Lab

Module 8: ChatGPT for detecting bugs

  • What types of bugs are easier to detect automatically?
  • Asking for help the right way

Hands-on Lab

Module 9: ChatGPT prompt engineering fundamentals

  • What is prompt engineering?
  • Why does ChatGPT understand some prompts better?
  • Tips and tricks for getting more consistent results

Hands-on Lab

Note:​​

Every student has assigned to him his own virtual lab environment setup.

Additional details:

To attend this course, you need to have:
• PC/Laptop with internet access
• Updated web browser

Register

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