AI
AI Empowered Software Development
This course explores how experienced software developers and teams can enhance their productivity dramatically through the use of modern AI tools such as LLMs (Large Language Models), coding assistants, co-pilots, development environment add-ons, simulated data generation tools, testing tools, deployment tools and collaboration tools – while maintaining code accuracy, security and responsibility.
Duration
2 days
Prerequisites
- Proficiency in Python, SQL, and basic software development workflows.
- Familiarity with development tools like Git, Docker, and IDEs.
In the duration of this course, students will gain:
- Mastery of AI tools and techniques to enhance software development productivity.
- Proficiency in applying Python and SQL with AI-powered assistants.
- Confidence in using AI for testing, deployment, and collaboration.
- Awareness of ethical and responsible AI development practices.
- Day 1: Foundations and Core Development Practices
- Morning Session (4 hours)
- Introduction to AI in Software Development (0.5 hour)
- Overview of AI’s role in modern software development.
- Key concepts: Large Language Models (LLMs), co-pilots, and AI-powered tools.
- Benefits: Productivity, accuracy, and collaboration.
- AI-Powered Coding Assistants and Development Environments (1.5 hours)
- Demonstration of coding assistants (e.g., GitHub Copilot, Tabnine).
- Hands-on: Writing Python functions with an AI coding assistant.
- Customizing IDEs with AI plugins.
- Responsible use of AI for maintaining code security and accuracy.
- Leveraging LLMs for Problem-Solving (1 hour)
- Using LLMs like ChatGPT for debugging, code reviews, and generating boilerplate code.
- Hands-on: Debugging Python scripts and generating SQL queries with LLMs.
- Understanding the limitations and potential biases in AI outputs.
- Data Generation and Preprocessing with AI (1 hour)
- Introduction to simulated data generation tools (e.g., Faker, GPT-generated datasets).
- Hands-on: Generating sample datasets for Python and SQL projects.
- Responsible handling of synthetic data for testing.
- Afternoon Session (4 hours)
- AI-Assisted Code Testing and QA (2 hours)
- Introduction to AI-powered testing tools (e.g., Codacy, DeepSource).
- Hands-on: Writing and optimizing test cases for Python and SQL code.
- Automating code linting and performance checks.
- Secure AI-Assisted Development Practices (2 hours)
- Understanding vulnerabilities introduced by AI-generated code.
- Strategies to ensure security and compliance.
- Case study: Identifying and mitigating security flaws in a Python/SQL application.
- AI-Assisted Code Testing and QA (2 hours)
- Introduction to AI in Software Development (0.5 hour)
- Morning Session (4 hours)
- Day 2: Advanced Applications and Team Integration
- Morning Session (4 hours)
- AI in Deployment and CI/CD (2 hours)
- Introduction to AI tools for DevOps (e.g., Harness, CircleCI plugins).
- Hands-on: Setting up a CI/CD pipeline enhanced with AI-driven optimizations.
- Automating deployment workflows for Python/SQL-based applications.
- Collaborative Development with AI (2 hours)
- AI-powered tools for team collaboration (e.g., Slack GPT, Google Bard integrations).
- Real-time code collaboration with AI add-ons.
- Managing version control and code reviews with AI insights.
- Hands-on: Collaborative project development using AI-powered platforms.
- Afternoon Session (4 hours)
- Advanced Prompting Techniques for LLMs (2.5 hours)
- Techniques for zero-shot, few-shot, and multi-shot prompting.
- Context setting and dynamic prompt engineering.
- Hands-on: Using Python and SQL prompts to solve complex problems.
- Building Responsible and Ethical AI Practices (1.0 hour)
- Importance of fairness, transparency, and accountability in AI-generated code.
- Guidelines for evaluating AI tools’ outputs responsibly.
- Ethical considerations in team settings.
- Recap and Q&A session (0.5 hour)
- Advanced Prompting Techniques for LLMs (2.5 hours)
- AI in Deployment and CI/CD (2 hours)
- Morning Session (4 hours)
Is there a discount available for current students?
UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.
What is the cancellation and refund policy?
Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.