Mastering Generative Ai : Google Gemini, Ibm Watson & Mcp
Published 8/2025
Created by SHANKAR NALLATHAMBI
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 20 Lectures ( 2h 26m ) | Size: 1 GB
Explain the core capabilities, strengths, and ideal use cases of Google Gemini, IBM Watson Analytics, and the Model Context Protocol (MCP).
Set up and confidently navigate Google Gemini and IBM Watson interfaces, including key settings, features, and workflow areas.
Apply clear prompt engineering frameworks to consistently generate high‑quality outputs in Gemini, including iterative refinement techniques.
Build practical no‑code automation workflows for tasks such as summarization, content drafting, data extraction, and productivity boosts using Gemini.
Import, explore, and prepare datasets in IBM Watson; create effective visualizations and communicate insights with clean, shareable dashboards.
Describe MCP fundamentals, architecture, and roles, and map common real‑world scenarios where MCP adds value-without writing code.
Plan and configure no‑code MCP‑enabled integrations to safely connect models with tools, data sources, and business workflows.
Compare Gemini vs. Watson for different tasks and select the right tool using clear decision criteria (data needs, output type, governance, and speed).
Execute iterative content generation workflows-from initial draft to structured review and finalization-using templates and checklists.
Identify and avoid common pitfalls across prompting, data hygiene, visualization clarity, and integration setup to ensure reliable outcomes.
Design intelligent, repeatable workflows that improve efficiency, reduce manual effort, and align with business or project goals.
Scope, plan, and present a mini capstone project that combines Gemini, Watson, and MCP, including goals, process, results, and next steps.
Requirements
Good news: there are no prerequisites. This course is designed for complete beginners and requires no coding, data science, or AI background.
zero experience in AI, analytics, or programming
Looking to apply AI practically without code
Description
This no-code course provides a structured, practical introduction to three pillars of modern generative AI: Google Gemini, IBM Watson Analytics, and the Model Context Protocol (MCP). Designed for all levels, it consists of 20 concise lessons (~7 minutes each) that progress from fundamentals to real-world applications. You will learn how to set up tools, craft effective prompts, explore and visualize data, and plan integrations-without any programming.What you'll learn across 20 topics:Introduction to Google Gemini: Understand Gemini's capabilities, core features, and where it excels.Getting started with Gemini: Simple setup steps, account options, and navigating key interfaces.Prompt engineering for Gemini: Clear frameworks for writing, refining, and testing prompts that deliver consistent results.Practical automation with Gemini: Time-saving workflows for drafting content, summarizing, and task optimization.IBM Watson Analytics overview: Orientation to the interface, terminology, and analytics workflow.Navigation and sections in Watson: How to import data, organize assets, and use dashboards efficiently.Data discovery and visualization: Exploratory analysis, visual best practices, and insight communication in Watson.Hands-on analytics (no code): Guided exercises using sample datasets to create charts, summaries, and shareable outputs.MCP fundamentals: What the Model Context Protocol is, why it matters, and common use cases.MCP principles and patterns: Core concepts, roles, and design patterns explained in plain language.MCP implementation (no code): Practical, tool-based approaches to configure and use MCP-enabled integrations.Standards and best practices: Governance, security basics, and emerging conventions around MCP.Choosing the right tool: Clear comparison of Gemini and Watson strengths to match the right tool to each task.MCP + Gemini: High-level integration scenarios to extend Gemini with tools and data safely and effectively.MCP + Watson: Practical ways to enhance analytics workflows and insights using MCP-enabled connections.Iterative content generation: Structured methods to draft, review, refine, and finalize AI outputs.Intelligent workflows for efficiency: Building repeatable, business-friendly processes that save time and reduce errors.Common mistakes to avoid: Practical guidance on prompt quality, data hygiene, and integration pitfalls.Advanced use cases: Realistic scenarios across content, analytics, research, and operations-no coding required.Capstone and next steps: A guided mini-project plan to combine Gemini, Watson, and MCP, plus checklists and resources.Who this course is for:Professionals, students, creators, and managers looking to apply AI in content, analytics, and automationAnyone seeking a clear, no-code path to practical AI skillsHow you'll learn:Short, focused lessons with step-by-step guidanceRepeatable templates, checklists, and workflowsRealistic examples you can adapt to your contextOutcomes:By the end of the course, you will be able to:Set up and navigate Gemini and Watson confidentlyWrite effective prompts and build iterative content workflowsExplore and visualize data to communicate insights clearlyUnderstand MCP and plan practical, no-code integrationsSelect the right tool for the job and avoid common mistakesNo coding experience is required. The course emphasizes clarity, decision-making, and dependable outcomes.
Who this course is for
Professionals, students, creators, or managers looking to apply AI practically without code
Beginners with zero experience in AI, analytics, or programming
Students and career changers exploring Generative AI fundamentals and real‑world applications
Business analysts and managers who want to turn data and prompts into clear, actionable outputs
Creators, freelancers, and entrepreneurs looking to automate content and workflows without programming
Team leads and non-technical stakeholders who need to evaluate AI tools and collaborate with technical teams
Educators and trainers building AI literacy programs or integrating AI into curricula
Anyone interested in Google Gemini, IBM Watson Analytics, and Model Context Protocol (MCP) without writing code
Mastering Generative Ai : Google Gemini, Ibm Watson & Mcp
