{"id":28,"date":"2026-05-13T18:37:35","date_gmt":"2026-05-13T18:37:35","guid":{"rendered":"https:\/\/airobotoedu.com\/?post_type=aire_program&#038;p=28"},"modified":"2026-07-10T19:39:50","modified_gmt":"2026-07-10T19:39:50","slug":"ai-machine-learning-developer","status":"publish","type":"aire_program","link":"https:\/\/airobotoedu.com\/?aire_program=ai-machine-learning-developer","title":{"rendered":"AI &amp; Machine Learning Developer"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">A 10-week applied program focused on the data and engineering skills needed to build generative AI systems \u2014 data pipelines, RAG, function calling, lightweight fine-tuning, AI agents, and end-to-end evaluation.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Program Goals<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Build the technical foundation needed for AI engineering and data engineering roles<\/li>\n\n\n\n<li>Prepare students to work with data pipelines that support LLMs and generative AI systems<\/li>\n\n\n\n<li>Develop applied experience with modern AI tools, model workflows, and evaluation practices<\/li>\n\n\n\n<li>Create a structured career pipeline for high-demand roles in AI systems<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Learning Outcomes<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Explain fundamentals of LLMs and the role of data in AI scaling<\/li>\n\n\n\n<li>Collect, extract, clean, label, and prepare data for generative AI<\/li>\n\n\n\n<li>Implement scalable data processing methods<\/li>\n\n\n\n<li>Use synthetic data and human data workflows<\/li>\n\n\n\n<li>Work with text, image, audio, and video pipelines<\/li>\n\n\n\n<li>Build retrieval-augmented generation (RAG) systems<\/li>\n\n\n\n<li>Apply function calling, orchestration, and evaluation methods<\/li>\n\n\n\n<li>Complete lightweight fine-tuning and summarization workflows<\/li>\n\n\n\n<li>Design and present an end-to-end capstone AI system<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">10-Week Course Schedule<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Week 1 \u2014 Foundations and Tooling:<\/strong> Generative AI landscape, LLM fundamentals, dev environments, data&#8217;s role in AI scaling.<\/li>\n\n\n\n<li><strong>Week 2 \u2014 Agent Workflows:<\/strong> AI agents, task decomposition, tool use, prompt patterns, human data workflows.<\/li>\n\n\n\n<li><strong>Week 3 \u2014 OCR, ASR, and TTS:<\/strong> Multimodal data extraction, OCR, speech-to-text, text-to-speech.<\/li>\n\n\n\n<li><strong>Week 4 \u2014 RAG Foundations:<\/strong> Retrieval-augmented generation, embeddings, vector databases, chunking strategies.<\/li>\n\n\n\n<li><strong>Week 5 \u2014 Hybrid Search &amp; Data Quality:<\/strong> Keyword search, semantic search, hybrid retrieval, filtering, visualization.<\/li>\n\n\n\n<li><strong>Week 6 \u2014 Function Calling:<\/strong> Structured outputs, tool\/function calling, schema design, reliability patterns.<\/li>\n\n\n\n<li><strong>Week 7 \u2014 Orchestration &amp; Evals:<\/strong> Workflow orchestration, evaluation design, model comparison, human-in-the-loop review.<\/li>\n\n\n\n<li><strong>Week 8 \u2014 Fine-Tuning &amp; Summarization:<\/strong> Lightweight fine-tuning, synthetic data generation, summarization pipelines.<\/li>\n\n\n\n<li><strong>Week 9 \u2014 Scaling AI Workflows:<\/strong> Data pipelines, databases, monitoring, cost\/performance tradeoffs.<\/li>\n\n\n\n<li><strong>Week 10 \u2014 Capstone:<\/strong> End-to-end AI system design, integration, presentation, reflection.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Capstone Project<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The capstone is an end-to-end AI system that integrates the major skills from the course. Each project includes a defined user problem, a data collection or extraction process, data cleaning\/filtering\/annotation, a model workflow (RAG, function calling, fine-tuning, or summarization), a clear evaluation plan, and a final presentation or demonstration.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Recommended Tools &amp; Technologies<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Python and common data libraries; APIs for large language models and generative AI systems; data storage and database tools; embedding and vector search tools; annotation and evaluation workflows; and development tools for reproducible projects.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Weekly Format<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Total commitment: 13.5 hours per week.<\/strong> Live lecture (2 hrs), hands-on programming lecture (1.5 hrs), office hours (1.5\u20132 hrs), weekly homework (~5 hrs), independent project work (~3.5\u20135.5 hrs).<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Who Should Enroll<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Senior undergraduate students preparing for applied AI engineering roles<\/li>\n\n\n\n<li>Technicians and engineers supporting AI-enabled operations<\/li>\n\n\n\n<li>Employers building internal AI capability<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>A 10-week applied program focused on the data and engineering skills needed to build generative AI systems \u2014 data pipelines, RAG, function calling, lightweight fine-tuning, AI agents, and end-to-end evaluation. Program Goals Learning Outcomes 10-Week Course Schedule Capstone Project The capstone is an end-to-end AI system that integrates the major skills from the course. Each [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":[],"class_list":["post-28","aire_program","type-aire_program","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/airobotoedu.com\/index.php?rest_route=\/wp\/v2\/aire_program\/28","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/airobotoedu.com\/index.php?rest_route=\/wp\/v2\/aire_program"}],"about":[{"href":"https:\/\/airobotoedu.com\/index.php?rest_route=\/wp\/v2\/types\/aire_program"}],"wp:attachment":[{"href":"https:\/\/airobotoedu.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=28"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}