
Master prompt engineering for developers by exploring natural language processing and language models, crafting intelligent, context-aware prompts, and applying them to code generation with Codewhisperer, GitHub Copilot, Tabnine, and Sourcegraph.
Master prompt engineering basics to guide language models and boost your development workflow. Learn how to generate code, tackle complex logic, and automate repetitive coding tasks with clear prompts.
Master prompting with respect to code snippets and placeholders to generate and refine code using language models, while reviewing Python outputs for correctness and security.
Learn to write code with ChatGPT or OpenAI by crafting specific prompts, iterating and refining, and reviewing code to generate Python functions like calculating a circle's area.
Learn to generate code and perform code reviews with ChatGPT using prompts in a chat interface, creating python snippets and project examples, with human review.
Learn to debug code with prompts in ChatGPT, applying a prompt formula to detect and fix errors, including division by zero in Python.
Learn to explain code with prompts using a simple step-by-step formula in ChatGPT, applying it to Python examples like swapping variables and grading systems.
Identify and fix syntax errors with prompts in ChatGPT, using 'update this code by rectifying the syntax for this code.' Covers averages, factorials, string conversion, and zero-division checks.
Learn to write functions with prompts using ChatGPT, gather user input, and generate code in Python and C++, including examples for rectangle area and random numbers.
generate classes in code with prompts using ChatGPT and explore defining objects with attributes and behaviors in Python and C++, including rectangle and student examples.
Discover Amazon Code Whisper, an AI coding companion that generates real-time single-line or full-function code suggestions in your IDE to build software faster and more securely.
Install the AWS toolkit in VS Code, sign in with a builder ID, and use CodeWhisperer to generate Python code suggestions.
Explore solving a California housing dataset machine learning project with Amazon's Code Whisperer using prompt engineering, covering data collection, exploration, preprocessing, model building, evaluation, and visualization.
Learn to build a Python snake game using AWS CodeWhisperer, importing pygame, initializing graphics, defining colors and window, and implementing score, game over messages, and drawing the snake.
Implement a Python snake game by building the main game loop, handling input events, moving and drawing the snake, placing food, and tracking score, using AWS Code Whisperer.
Explore GitHub Copilot, an AI-powered coding assistant by OpenAI and GitHub, delivering real-time code suggestions and seamless editor integration, supporting Python, JavaScript, Java, and Go.
Learn how GitHub Copilot generates functions, classes, and algorithms from prompts to accelerate code creation. See a seconds-in-a-day function, a car class, and an insertion sort example.
Learn to solve a mini project with GitHub Copilot in Visual Studio Code by building a smart password generator in Python that creates strong, unique passwords using random and string.
Explore building a tic tac toe game with prompts in GitHub Copilot, including printing the board, checking rows, columns, diagonals, validating moves, updating the board, and detecting wins or ties.
Explore how to set up Tab nine inside Visual Studio Code, including installing the extension, signing in, and using in-editor code suggestions to accelerate development.
Learn to solve real life coding scenarios with Tabnine in VS Code by building a Python YouTube video downloader that downloads videos in the highest resolution.
Design the back end using prompts to fetch current weather and five-day forecasts, managing migrations and api keys, and render a template with city input and helper functions.
Design and style the weather app front end with Django templates and Jinja, implement static css, and build a two-city compare weather feature with a five-day forecast.
Explore Sourcegraph Cody, a one-stop solution for efficient code search, understanding, and intelligence. Learn how it explains complex regex in plain English, aids debugging, and helps you grok your code.
Explore how Sourcegraph Cody in VS Code explains code, detects code smells, generates unit tests, improves variable names, and translates across Python, TypeScript, Go, JavaScript, and HTML.
A beginner guide to prompt engineering for developers introduces prompt types and problem-solving strategies, equipping you with critical thinking skills to tackle real-world challenges and make a positive societal impact.
Get ready for "Prompt Engineering for Developers: A Comprehensive Course for Beginners." This course will introduce you to the fascinating world of prompt engineering, empowering developers to optimize language models like ChatGPT for specific tasks and domains. Prompt engineering allows you to fine-tune language models and craft customized prompts to elicit desired responses.
This cutting-edge course is designed to equip developers with the essential skills and knowledge required to harness the power of AI language models and specifically all AI tools, to revolutionize their development process. As technology continues to evolve, AI language models have emerged as indispensable tools for developers seeking to create innovative and intelligent applications. Whether you're an experienced programmer looking to expand your repertoire or a newcomer eager to explore the realm of artificial intelligence, this course will empower you to utilize prompts effectively, optimize model outputs, and explore the full potential of AI language models in your projects.
Throughout this course, you'll delve into the inner workings of prompt engineering, gaining a profound understanding of its architecture and capabilities. From constructing sophisticated prompts that yield accurate and contextually relevant responses to fine-tuning models for specialized applications, our comprehensive curriculum covers every facet of prompt engineering. The hands-on nature of this course ensures that you'll have ample opportunities to put your newfound knowledge into practice, embarking on thrilling projects that leverage AI to build innovative solutions. Embark on this journey into the realm of prompt engineering, and unlock a world of possibilities to enhance your development skills and create groundbreaking applications.
Course Overview:
Prompt engineering is a powerful concept that enables developers to tailor language models' behavior by providing context or instructions in the form of prompts. In this comprehensive course, you will explore the fundamentals of prompt engineering and gain hands-on experience in creating effective prompts for language models.
Hands-On Learning:
The "Prompt Engineering for Developers" course focuses on practical learning with a series of hands-on exercises and labs. Through interactive sessions, you will work directly with language models, crafting and refining prompts to influence their outputs. This hands-on approach will deepen your understanding and skill in prompt engineering.
Who Should Enroll:
This course is designed for developers, AI practitioners, NLP enthusiasts, and anyone eager to optimize language models for specific tasks. Whether you are new to prompt engineering or seeking to enhance your expertise, this course will equip you with valuable insights and practical techniques.
Prerequisites:
Basic understanding of natural language processing (NLP) concepts is recommended.
Familiarity with working with language models.
Little Proficiency in a programming language.
You'll be implementing prompt engineering techniques using different prompting libraries.
What You'll Learn:
Throughout the course, you will:
Discover the significance of prompt engineering in tailoring language models' responses.
Explore various prompt engineering techniques to achieve specific task-oriented outputs.
Learn how to evaluate and iterate on prompts to improve language model performance.
Gain insights into best practices for creating effective prompts and obtaining reliable model responses.
Course Structure:
The course comprises approximately 30 labs, starting with foundational concepts and gradually progressing to advanced prompt engineering techniques. Each lab will provide hands-on exercises, ensuring that you gain practical experience in prompt engineering.
Who This Course is For:
Ideal for developers, AI practitioners, and NLP enthusiasts seeking to enhance prompt engineering skills.
Suitable for those interested in automating tasks, generating specialized content, fine-tuning model behavior, or addressing specific use cases.
Empowers learners to optimize language models and craft effective prompts for various tasks.
Embark on an exciting journey into the world of prompt engineering and unleash the full potential of language models.
For those who want to gain expertise in prompt engineering techniques by the end of the course.
Students who want to apply learned skills to enhance language models for your projects and applications.