AI Portfolio in 2025: Build 12 AI end-to-end AI Products

Get ahead with the hands-on experience of the most essential skill of 2025- AI Literacy (Gen AI & Agentic AI Included)

What you'll learn
- Get hands-on experience in the most in-demand skill of 2025- AI Literacy
- 12 End to End Use Cases on AI, Gen AI & Agentic AI Covered
- Get full codebase access plus 100 ChatGPT prompt templates for daily use
- Practice quizzes to reinforce concepts

Requirements
- There are no mandatory prerequisites. However, if you are completely new to AI or do not come from a technical background, we strongly recommend starting with our “Foundations of AI Literacy (For Non-AI Professionals)” course. It is Part 1 of this specialization and helps you build a clear understanding of the basics before diving into real-world projects.

Description
The AI Literacy Specialization Program isone-of-a-kindhierarchical & cognitive skills based curriculum that teaches artificial intelligence (AI) based on a scientific framework broken down into four levels of cognitive skills.

Part 2: Use & Applycombines the below two cognitive skills -

Using(practicing AI concepts in realistic environments)

Applying(adapting AI knowledge to solve real-world problems)

This part of the program emphasizespractical implementationandhands-on skill-buildingthrough structured exercises and applied use cases. It includes3 core competencies, each supported by detailed performance indicators, totaling20. These are designed to ensure learners are able to confidently navigate and apply AI technologies in varied contexts.

Competency Overview

1) Traditional AI

This competency focuses on foundational AI methods developed before the deep learning era and includes core machine learning approaches. Learners will understand the end-to-end AI workflow and the different layers involved in building traditional AI systems.

Performance Indicators:

Understanding the AI Technology Stack

Application Layer: User interface and business application logic

Model Layer: Machine learning algorithms and training logic

Infrastructure Layer: Cloud platforms, hardware accelerators, and deployment tools

Common Components: Data pipelines, model monitoring, and governance

Choosing the Right Tech Stack for Business Use Cases

End to end Use Cases:

Credit Card Default Prediction

Housing Price Prediction

Segmentation for Online Retail

NLP Based Resume to JD Matcher

CV Based Car Type Detection

2) Generative AI

This competency introduces learners to cutting-edge generative AI tools and techniques, including how large language models (LLMs) and diffusion models are built and adapted. The focus is on responsible usage, design of prompts, and system integration.

Performance Indicators:

Understanding the Generative AI Technology Stack

Prompt Engineering (PE) – Basics (Prompt types, templates, prompt chaining)

Resume Customizer Tool

Ideation with ChatGPT

Design using Gamma

Build and Deploy using Lovable

Market with HubSpot

Maintain with Gemini for Sheets

Prompt Engineering – Advanced (Context management, few-shot prompting, evaluation)

Resume Customizer Tool using API

Retrieval-Augmented Generation (RAG) – Using external knowledge with LLMs

RAG Based Resume to JD Matcher

Fine-tuning – Customizing pre-trained models for specific enterprise or domain needs

3) Agentic AI

This competency focuses on the emerging paradigm of AI agents – systems that can reason, plan, and act autonomously within defined boundaries. It helps learners understand how to orchestrate multi-step tasks using AI tools.

Performance Indicators:

Understanding the Agentic AI Architecture

Vibe Coding 101

No Code Agent Builders

AI News Summarizer:

Using ChatGPT UI & CustomGPT Builder

Using Replit

Using n8n

Code Based Agentic AI

Credit Card Default Prediction using Cursor

Agentic AI in the Workplace

By completing Part 2 of the AI Literacy Specialization Program, participants will:

Gainpractical experiencein building and deploying AI models across different domains

Be equipped toselect and apply the right AI techniquesfor specific business problems

Understand thetechnical and ethical dimensionsof applying both traditional and generative AI

Be capable of designing AI workflows andinterfacing with technical teamsconfidently

Build readiness totransition into advanced AI rolesor contribute meaningfully to AI projects in non-technical roles

Who this course is for:
- AI enthusiasts or career switchers who want to build an AI portfolio and learn by doing
- Business analysts aiming to integrate AI into internal tools and automate decision-making with no-code and low-code solutions.
- Solopreneurs & Product managers looking to prototype AI features, collaborate better with tech teams, and turn ideas into working tools without coding from scratch.
- Data scientists who want to go beyond model training and learn how to build AI agents and automate real-world workflows.
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