GenAI for Software Developers Course
Format: Online, on-demand, self paced
Time Commitment: 10 hours/week for 10 weeks
Format: Online, on-demand, self paced
Time Commitment: 10 hours/week for 10 weeks
A skillset in AI in the current market will increase your salary by as much as
40%
Source: University of Oxford
SWE leader roles will explicitly require oversight of AI in more than
50% of positions
Source: Gartner
Employers experiencing sourcing challenges for AI roles due to lack of talent
2 out of 3
Source: Analytics Insight
Attend bi-monthly group coaching sessions and workshops, as well as weekly office hours hosted by our GenAI expert and course instructor, Pace Ellsworth.
You’ll be added to a small study group with several other learners in the course, whom you can lean on for support, problem-solving, motivation and accountability.
Get ongoing support from a/A staff and peers with dedicated channels for curriculum topics. Connect with others, discuss AI trends, explore job opportunities, and build your network.
Designed in collaboration with AI experts to address immediate needs in your current role, helping you to quickly integrate AI tools and techniques into your daily workflows.
Combines AI-powered software development and generative AI engineering, covering a wide range of AI use cases.
Emphasizes hands-on learning with two capstone portfolio-ready projects and 10+ mini projects.
Covers the latest AI tools, including LangChain, LLMOps, RAG workflows, and more.
Learn when you can, at your own pace.
Learn more about the possibilities within AI-powered development with our GenAI Survival Kit.
We designed this course for:
Software Engineers and Developers looking to build complex LLM applications and accelerate their existing processes with AI.
Data Scientists and Machine Learning Engineers whose aim is to transition into a full-stack AI practitioner.
AI Enthusiasts and Aspiring AI Engineers wanting to start a career in AI or enhance their current skill set.
Intermediate programming knowledge, including proficiency in Python
Cloud computing basics and an understanding of web development
Foundational software development knowledge
Basic understanding of AI and machine learning
Experience with data handling and analysis
Comfortability with problem-solving and logical thinking
Part 1: AI-Powered Software Development
Embark on a learning journey focused on transforming the entire software development lifecycle with AI tools. This part concludes with a capstone project where you'll apply these tools to develop a fully AI-powered software solution.
• Introduction to Generative AI for Software Development: Understand the core principles of generative AI and its applications in software development.
• Advanced Prompt Engineering for Effective AI Integration: Learn advanced techniques for prompt engineering to optimize AI outputs.
• Strategic Planning in Software Development with AI: Use AI for strategic decision-making, project planning, and resource allocation.
• AI-Enhanced Design and Architecture: Leverage AI tools to enhance design and architecture, creating smarter, more adaptable systems.
• Automated Code Generation and Synthesis with AI: Use AI to generate and synthesize code, reducing manual effort.
• AI-Driven Code Optimization and Refactoring: Optimize code quality and performance with AI-driven tools.
• Intelligent Documentation Generation Using AI: Automate documentation processes for consistency and efficiency.
• Enhancing Unit Testing with AI Techniques: Integrate AI into unit testing for better coverage and efficiency.
• Automating Test Case Generation with AI: Use AI to automate the creation of test cases.
• AI-Augmented Visual Testing and Validation: Implement AI-driven visual testing for a seamless user experience.
• Intelligent Deployment Automation with AI-Generated Scripts: Automate deployment with AI-generated scripts.
• AI-Driven Optimization of Deployment Pipelines: Enhance deployment efficiency with AI.
• AI-Enabled Software Monitoring and Analytics: Monitor software performance using AI tools.
• Proactive Troubleshooting and Incident Management with AI: Use AI for proactive troubleshooting and incident management.
Apply your knowledge in a practical capstone project that integrates all aspects of AI-powered software development, from planning and design to testing and deployment.
Part 2: Building Generative AI Applications
Dive deeper into the world of generative AI and LLMs. Progress through advanced modules on multi-agent systems, embedding fine-tuning, and LLM operations to master the deployment of sophisticated AI applications. This part culminates in a capstone project to design and present a comprehensive AI application.
• Introduction to Generative AI Development: Learn the basics of generative AI, its applications, and its industry impact.
• Fundamentals of LLM Architecture and Applications: Gain insights into LLM architectures and their practical uses.
• Advanced Techniques in Prompt Engineering: Master techniques for fine-tuning LLM outputs for specific use cases.
• Building Blocks of RAG: Embeddings and Vector-Based Retrieval: Learn foundational concepts for developing RAG systems.
• Implementing RAG Workflows with LangChain: Build and manage RAG workflows using the LangChain framework.
• Deploying and Scaling RAG Systems in Production Environments: Discover best practices for deploying and scaling RAG systems.
• Integrating LLM Agents with External Tools and APIs: Enable LLM agents to interact with external tools and APIs.
• Developing Agent-Based Applications with LangGraph: Build agent-based applications using LangGraph.
• Designing and Implementing Multi-Agent Systems for Complex Problem Solving: Create multi-agent systems for solving intricate problems.
• Fine-Tuning Techniques for Domain-Specific Embeddings: Learn techniques for fine-tuning LLM embeddings.
• LLM Operations (LLMOps): Deployment, Monitoring, and Continuous Improvement: Master best practices for deploying and optimizing LLMs.
Create a complete AI application that integrates advanced generative AI techniques, LLMs, and multi-agent systems to solve a real-world problem.
This course will equip you with hands-on experience with a wide range of cutting-edge tools and technologies essential for AI-powered software development and generative AI engineering, including:
Meet Pace Ellsworth, our GenAI expert and course instructor. Pace is a Cherokee Native tech program lead, and experienced full-stack developer, with a passion for automation and 15+ years in startups and enterprises like Logitech, Best Buy, and IMAX. He currently serves as CEO at his own AI startup PRE (Preserving Records Everywhere), where he is focused on preserving cultural heritage through developing a RAG-based social asset network to address the challenges of loneliness, AI bias, and the generation gap. He can’t wait to partner with you and help you master the tools needed to create exponential impacts in your role and bridge digital divides. As a learner in the course, you’ll be able to lean on Pace:
• During Bi-Weekly Small Group Coaching Workshops
• In Weekly Q&A Sessions
• Anytime, 1:1 in our Private Discord Community
You'll be able to
Understand AI fundamentals and use generative AI tools like LLMs to enhance software development workflows
Implement AI-driven testing methods to increase coverage, efficiency, and reliability.
Build generative AI applications using LLMs, RAG systems, and multi-agent frameworks.
Optimize AI models and systems for performance, scalability, and continuous improvement.
Utilize AI tools for strategic decision-making, project planning, and architecture design.
Solve complex problems, drive innovation, and develop new AI-powered solutions.
You’ll be qualified to be a:
Average pay range
$200K - $311K/yr*
Average pay range
$158K - $254K/yr*
Average pay range
$112K - $179K/yr*
*Source: Glassdoor salaries as of August 2024
Join Pace Ellsworth (our GenAI expert and course instructor) and several of your peers, for coaching on topics like: building a code generation tool using generative AI, automating software deployment with AI-generated scripts and more.
Our GenAI expert and course instructor, Pace Ellsworth will lead these hour-long sessions and answer any questions learners have live on the call.
Connect and converse with your small group and other peers in the course about specific curriculum topics, AI trends, job opportunities, etc.
Get answers to your technical questions from course developers and other AI experts in real-time.
Receive immediate feedback on any basic administrative or enrollment management questions
• GitHub Copilot: An AI-powered code completion tool that assists with code generation and streamlining the development process.
• Katalon AI: A platform for automated testing that utilizes AI to generate comprehensive and efficient test cases.
• Eraser AI: An AI tool to enhance technical communication, transforming documentation into diagrams and refining content.
• Snyk AI: An AI-driven security tool integrated into CI/CD pipelines to ensure code security and vulnerability management.
• New Relic AI: A monitoring and observability platform leveraging AI to analyze performance, diagnose issues, and maintain software health.
• Google Cloud Run: A fully managed serverless platform that allows the deployment of containerized applications using AI-based services.
• OpenAI: A leading AI research and deployment company providing models like GPT-3, used for advanced generative AI applications.
• Google Gemini: A generative AI toolset from Google focused on LLMs and AI-driven insights for advanced applications.
• Crew AI: A platform for managing multi-agent AI systems, enabling sophisticated AI interactions and workflows.
• LangChain: A framework for developing LLM-powered applications by chaining multiple AI components together.
• LangSmith: A tool to manage and optimize the development of AI applications within the LangChain ecosystem.
• LangGraph: A framework for orchestrating multiple AI agents and their interactions to solve complex problems.
• Weights and Biases: A tool for tracking and optimizing machine learning experiments, including those involving LLMs and generative AI.
• Hugging Face: A platform providing access to open-source AI models, including transformers, for natural language processing and understanding.
• Tavily: A platform for creating AI-powered virtual assistants and chatbots to enhance customer experience and interaction.
• LlamaIndex: A library for fine-tuning and deploying LLMs, focusing on domain-specific applications and performance optimization.
• Weaviate: An open-source vector search engine optimized for retrieval-augmented generation (RAG) systems, enabling efficient data retrieval.
• Advanced AI Proficiency: Master the application of AI tools across diverse software development and AI engineering contexts.
• Hands-On Experience: Develop real-world skills through capstone projects and mini-projects.
• Increased Productivity and Efficiency: Leverage AI to automate tasks, optimize workflows, and enhance code quality.
• Career Advancement: Enhance employability by acquiring cutting-edge skills in AI-driven software development and generative AI engineering.
• Adaptability to Future Trends: Stay ahead of technological advancements by mastering the latest AI tools and methodologies.
Fill out our course application and enter coupon code EARLYBIRD at checkout. Ends October 31st.
Please feel free to reach out to us at any time at aisupport@appacademy.io and we’ll be happy to help.
You will be able to complete the course and access the content for 10 weeks, starting the day you make your payment.
Master the cutting-edge AI skills that employers are looking for and increase your earnings potential drastically! All it will take is just 10 weeks.