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Dive into advanced Retrieval-Augmented Generation (RAG) techniques, vector databases, and retrievers to build intelligent search applications with FAISS, ChromaDB, and LangChain for improved AI-powered solutions.
Explore how generative AI revolutionizes data engineering, enhancing productivity in architecture design, querying, schema design, data augmentation, pipelines, and analysis. Gain hands-on skills for real-world applications.
Explore database management, SQL basics, and security strategies. Learn to identify and mitigate injection vulnerabilities. Gain hands-on experience in user management, access control, and encryption.
Learn essential COBOL features including numeric usage, editing, structured programming, table handling, and intrinsic functions. Develop skills in debugging, report creation, and writing maintainable code.
Comprehensive practice exams for CompTIA A+ Core 1 & 2 certification, covering key IT domains and testing strategies to enhance readiness for the official exam.
Learn core IBM COBOL software development practices, including code documentation, working with existing code, quality assurance, technical support, and project management for enhanced programming skills.
Master multimodal AI development by integrating text, speech, images, and video using tools like IBM Granite, OpenAI's Whisper, DALL·E, and Meta's Llama to build interactive applications with Python, Flask, and Gradio.
Explore Apache Spark, Docker, and Watson Machine Learning for enterprise model deployment. Learn best practices for data manipulation, model training, and tuning, focusing on recommender systems and scalable solutions.
Develop a responsive website using HTML, CSS, and React. Design layouts, create dynamic components, and deploy a fully functional site to enhance your web development portfolio.
Master ethical hacking with Kali Linux through hands-on training in installation, security tools, and automation scripting. Learn to conduct penetration testing, vulnerability analysis, and customize tools using Python and Bash.
Learn to implement DataOps methodology for high-quality enterprise data, enabling AI and driving value. Covers data governance, model management, and best practices for delivering trusted data across an organization.
Hands-on training in deploying AI models to production using Docker, Kubernetes, and IBM tools. Learn to build APIs, monitor performance, and iterate efficiently in enterprise AI workflows.
Master generative AI for digital marketing: create content, optimize ads, enhance SEO, improve e-commerce, and personalize email campaigns while addressing ethical considerations.
Explore cloud-native app development, DevOps culture, Agile methodologies, and NoSQL databases. Gain hands-on experience deploying and modernizing applications using CI/CD practices and industry-standard tools.
Develop robust RESTful APIs with Node.js and MongoDB. Learn database design, CRUD operations, authentication, error handling, and deployment for scalable cloud-native applications.
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