Cloud Computing with AI Integration Course
Learn to deploy, manage, and scale AI models using cloud platforms like AWS, Azure, and Google Cloud.
- Cloud fundamentals (IaaS, PaaS, SaaS)
- AI/ML model deployment in the cloud
- Serverless computing & microservices
- Cost optimization & cloud security
Core Subjects
Mathematics and Statistics:
Essential topics include linear algebra, calculus, probability, and inferential statistics.
Programming:
Proficiency in languages like Python (with libraries such as Pandas and NumPy) and SQL is crucial for data manipulation and analysis.
Data Wrangling and Preprocessing:
This involves cleaning, transforming, and handling missing values in raw data.
Exploratory Data Analysis (EDA):
Focuses on summarizing data and uncovering patterns using descriptive statistics and visualization tools like Matplotlib and Seaborn.
Machine Learning:
Covers algorithms, models, and techniques for building predictive systems, including concepts like model evaluation, regularization, and hyperparameter tuning.
Data Visualization:
Teaches how to create charts, graphs, and interactive dashboards to communicate insights using tools like Tableau or Power BI
Advanced and Specialized Topics
Big Data Technologies
Introduces tools and techniques for working with large datasets.
Cloud Computing
Covers how to use platforms like AWS or Azure for data science tasks.
Deep Learning
An advanced area that may be an elective, focusing on neural networks.
Natural Language Processing (NLP)
Involves techniques for processing and analyzing text data.
Ethics and Data Privacy
A key component that addresses responsible data handling.
Capstones Projects
Often required to apply learned skills to a real-world problem
Master AI and Data Science
Topics Covered:
- What is AI and Generative AI
- Understanding Large Language Models (LLMs)
- Basics of Prompt Crafting
- Hands-on with ChatGPT and Copilot
- Writing effective zero-shot and few-shot prompts
- Tone and style control in responses
- Tools: ChatGPT, Copilot
Topics Covered:
- Chain-of-Thought and Multi-Step Reasoning
- System and Instruction Prompts
- Context Management and Memory in Prompts
- Building Domain-Specific Prompts (e.g., for marketing, data, or education)
- Writing effective zero-shot and few-shot prompts
- Case Studies and Practice
Tools: ChatGPT (GPT-4), Perplexity, Copilot
Topics Covered:
- Data Cleaning and Preprocessing with AI
- Exploring Datasets using Copilot and Excel
- Using AI for Statistical Analysis
- Deriving Insights from Large Datasets
- AI-powered Decision Making
Tools: Excel Copilot, ChatGPT, n8n
Topics Covered:
- AI-generated Summaries and Reports
- Converting Numbers into Narratives
- Creating Visual Dashboards
- Designing AI-powered Presentations
- Telling Stories with Data
Tools: Copilot, Synthesia, HeyGen
Topics Covered:
- Understanding Text-to-Image Models
- Creating Visual Concepts and Illustrations
- Image Enhancement and AI Editing
- Branding and Design with AI Images
Tools: DALL·E, Midjourney, Runway
Topics Covered:
- AI-Assisted UI/UX Design
- Mockup Generation using Prompts
- AI Wireframing and Testing
- Iterative Design with AI Feedback
- Project Showcase: Build Your Prototype
Tools: Lovable, Runway, Figma (AI-integrated), n8n
Topics Covered:
- AI Voice Generation and Editing
- Video Creation with AI Avatars
- Workflow Automation using AI Tools
- Integrating Tools for End-to-End Projects
- Telling Stories with Data
Tools: ElevenLabs, HeyGen, Synthesia, n8n
Topics Covered:
- Create a data-driven AI dashboard
- Build an AI-powered business assistant
- Generate an automated storytelling video
- Prototype a product using AI design tools
Deliverables:
- Final Prototype
- Report & Presentation
- Portfolio-Ready Project
Master 15+ Top AI tools
By the end of this course, learners will:
🎯 Certification Outcome
Master 15+ Top AI Tools
Write, Optimize, and Evaluate AI Prompts
Design AI-Powered Prototypes and Visual Outputs
Build a Strong Portfolio and Enhance CV & LinkedIn Profile
Register Now!
AI is getting trained every day. Are you?
With rapid advancements in automation and artificial intelligence, it’s estimated that nearly 69% of all current IT jobs in India will be automated by 2030. The future belongs to those who upgrade their skills and learn how to work with AI, not against it.