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EngX AI-Supported Software EngineeringIntegrate GitHub Copilot and ChatGPT into your daily work for streamlined, efficient development.
Skills covered
Engineering Practices

The discount applies for the first 100 participants

Money-back guarantee — 30 days after purchase

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    Course rating

    4.8 / 5

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    Course format

    Self-paced course

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    Course level

    Basic to intermediate

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    Course language


Knowledge you will gain
checkmarkLLM basics

Introduction to the concept of AI, ML, natural language processing, and large language models.

checkmarkDevelopment tasks

Creating a new function, class/service, or module/project. Using AI to explain, refactor, or modify code fragments.

checkmarkGitHub Copilot and ChatGPT

Conversational and inline AI tools. Benefits, limitations, typical use cases, and prompt examples for both types.

checkmarkProject documentation

Creating project and source code documentation, including inline comments, structured class and method comments.

checkmarkPrompt engineering

Prompt structure, parameters, types, and main techniques to streamline daily dev tasks and maintain the result quality.

checkmarkDevelopment testing

Test creation and maintenance with a focus on unit tests. Prompts for generating new test data in CSV or source code.

Languages used for course practiceThe dev tasks are designed for those programming languages.
Study plan
  • 5 modules
  • 14 theory lessons
  • 9 practice tasks
  • 7 h 30 min
1AI-supported engineering
  • 1 lesson
  • 7 min
file-text-20.svgCourse introduction

7 min

2Mastering LLMs
  • 6 lessons
  • 2 h 30 min
  • 4 lessons
  • 6 practice tasks
  • 6 h
4Development testing
  • 2 lessons
  • 2 practice tasks
  • 1 h
5Technical documentation
  • 1 lesson
  • 1 practice task
  • 35 min
  • This course is a great balance between theory and practice that enables usage of LLM and GenAI into my everyday life, be it at work, or in a regular life. It has been a few months that I have taken the course and since then I use LLM almost every day. The course covers LLM use in several aspects of Software Development Life Cycle such as Development, Refactoring, Testing, etc. When doing the course, I have reflected many times that I could save hours of work have done previously if I had known the techniques and power of LLM.

    Khachatur Tovmasyanlinkedin.svg
    Lead Software EngineeratEPAM Systems
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  • I’m truly amazed by the course’s in-depth, hands-on approach to AI in software engineering. Its successful blend of theory and practice enabled me to utilize AI tools for tasks like code refactoring, creating test data and technical documentation, and offered valuable insights into Large Language Models (LLMs). However, I’d have appreciated more content on using and creating LLMs, considering the fast-paced evolution in the AI and Machine Learning field. Despite this, I highly recommend this course for anyone keen to stay updated with the latest AI tools and techniques. It offers a unique, practical learning experience that's immediately applicable to your day-to-day engineering tasks.

    Chandan Varshneylinkedin.svg
    Lead Software Development Test Automation EngineeratEPAM Systems
Course experts
  • Alexey Shcheglov
    Project Manager
    Project Manager with 20+ years in software, transforming best engineering practices into actionable courses, head of EngX educational programs.
  • Dmytro Pavliuk
    Delivery Manager
    Delivery Manager with 17 years in software, proficient in management, SDLC, Java, and AWS. Contributed to AI integration into SDLC and 3 AI learning courses.
  • Oleksandr Ponikarov
    Senior Engineering Manager
    Senior Manager with 15+ years in software. Responsible for global mentoring, BigData discipline development, and people management at EPAM.
  • Igor Derkach
    Senior Software Engineering Manager
    Experienced Java trainer and courses author, excelling in large-scale project development and management.
  • Aliaksandr Trafimenkalinkedin.svg
    Senior Engineering Manager
    Senior Manager leading innovative projects and mentoring tech talent in engineering and AI applications at EPAM's Microsoft Technology Division.
  • Pavel Kiadrynski
    Lead Software Engineer
    Lead Software Engineer excelling in Python. Has experience in data science and creating corporate MDM solutions.
  • Timur Polishchuklinkedin.svg
    Software Engineer
    Software Engineer with a diverse skill set in software development, debugging, project leadership, and new technologies adoption — such as integrating LLMs into business processes.
  • Alexander Shvarzlinkedin.svg
    Software Engineering Team Leader
    Senior Team Leader with 20 years of IT experience, specializing in Java, microservices, Google Cloud Platform, and system migration.
  • Vadym Korotkyilinkedin.svg
    Delivery Manager
    Delivery Manager, co-head of JavaScript Learning and Development node and AI Coach at EPAM, focusing on enabling AI projects.
  • Maxim Belov
    Software Engineering Team Leader
    Python Competency Manager at EPAM, coordinating Python competency and Learning and Development node, with a mission to make Python accessible to all.
Frequently asked questions
Who will check my practice tasks?
Can I take the course if I don’t code in Java, Javascript, Python, or C#?
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Is it possible to update the email used for accessing the course?
I lost my credentials. How can I restore them?
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Can I share my course access with family and friends?