Added draft for the first blog post (SkillsBuild courses)

Author: Andrei-Constantin-Programmer

content/posts/team-intro-ibm-skillsbuild.md

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+date = '2025-06-16T19:43:25+01:00'
+draft = true
+title = 'Building Our Foundation: AI SkillsBuild Certifications'
+tags = ["AI", "LLM", "SkillsBuild", "IBM", "Team Learning", "RAG", "Watsonx", "Embeddings", "Granite"]
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+
+Welcome to the official blog for our UCL MSc project in collaboration with IBM!  
+Over the coming weeks, we'll share progress updates, key learnings, and reflections as we build an AI-powered tool to help modernise legacy software systems.
+
+## 1. Introduction
+To effectively design and implement an AI-powered tool for refactoring legacy software, we knew we had to establish a shared understanding of key AI concepts, fast.
+
+Instead of diving straight into building, our team took a structured approach: we enrolled in IBM SkillsBuild’s AI and Collaboration pathways. These courses gave us a practical introduction to current AI tools and practices, with a special focus on the capabilities of IBM watsonx and Granite models.
+
+We approached this not as a checklist, but as a multi-pronged strategy. Each team member explored different AI courses to diversify our understanding and avoid redundancy.
+
+## 2. AI Pathway
+Each member selected different courses based on their existing expertise and interest. This ensured our combined knowledge was deeper and wider.
+
+- Getting Started with Artificial Intelligence - A broad overview of AI's key concepts, terminology, and history.
+
+- IBM Granite Models for Software Development - An in-depth look at IBM’s foundation models and their relevance to real-world developer workflows.
+
+- Unleashing the Power of AI Agents - Explored how autonomous agents can extend LLMs' utility through goal-driven reasoning.
+
+- Introduction to Retrieval Augmented Generation - Introduced RAG as a solution to LLM hallucination and domain-specific augmentation.
+
+- Vector Embeddings: AI’s Key to Meaning - Covered how embeddings allow semantic understanding and similarity search in AI systems.
+
+- Use Generative AI for Software Development Using IBM watsonx - Hands-on introduction to watsonx tools applied to code generation and transformation.
+
+- Introduction to Large Language Models - Established a grounding in how LLMs work under the hood, including architecture and limitations.
+
+## 3. Collaboration Pathway
+All members also completed:
+
+Design Thinking – Learning to centre user needs, iterate quickly, and ideate without bias.
+
+Agile Explorer – Refreshing agile values and practices for real-world software development.
+
+These helped align our workflows and team dynamics - especially important as we begin working with collaborative tooling.
+