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Build responsive website components with Bootstrap: set up the framework, apply key classes, components and icons, create grid layouts, and style a React app.
Build a recommendation system with ChromaDB: create collections, manage embeddings from a Hugging Face model, and run similarity searches that power RAG retrieval.
Build a food recommendation system with Chroma DB: create collections, manage embeddings, and run similarity searches that power retrieval in RAG applications.
Evaluate and build models for a streaming media use case: regression and classification metrics, tree-based ensembles, TensorFlow neural nets, Watson Visual Recognition and NLU.
Combine SEO fundamentals with generative AI: run keyword research, on-page and technical optimization, AI content generation, predictive analytics, and Generative Engine Optimization in a capstone project.
Dissect malware through static and dynamic analysis, manual code reversing of PowerShell, JavaScript, macro documents, ELF, webshell and JAR files, plus Win32 Assembly fundamentals.
Explore digital marketing strategy: select channels such as SEO, social media, PPC and email, build audience personas with Semrush, and track traffic, conversions, ROI and engagement.
Apply feature engineering best practices: handle class imbalance, detect model bias with AI Fairness 360, reduce dimensions, flag outliers, and explore text through topic modeling.
Produce 16 product management artifacts for a given scenario, from Ansoff matrix, PRD and roadmap to business case, demand generation and end-of-life plans, with peer review.
Build Java applications using encapsulation, inheritance, polymorphism, interfaces, and the collections framework, handling files, directories, and date-time operations in a mood-tracking final project.
Build end-to-end RAG applications: implement multi-query, self-querying and parent document retrievers with LangChain, run similarity search in FAISS and Chroma DB, and add a Gradio UI.
Build vector database applications with Chroma DB, MongoDB, Cassandra, and PostgreSQL: create embeddings and collections, run similarity searches, and ship a RAG-powered recommendation capstone.
Learn the software development lifecycle for COBOL and IBM z/OS environments: SDLC phases, Agile/Scrum, systems analysis, IBM system architectures, pseudocode, structured design, and unit testing.
Learn relational and non-relational database concepts, write basic SQL, and secure data with encryption, hashing, masking, tokenization, and defenses against OS command and SQL injection.
Apply generative AI across data engineering work: design warehouse schemas and infrastructure, query databases, build ETL pipelines, augment and anonymize data, and weigh ethical risks.
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