Applied Artificial Intelligence and Machine Learning
Program Overview
Artificial Intelligence and Machine Learning are transforming every industry—from healthcare and finance to e-commerce and automation. This AI-ML program is designed to help students gain deep technical expertise in machine learning, data analytics, neural networks, and AI-driven decision making.
Whether you aim to become a Data Scientist, ML Engineer, or AI Product Manager, this program empowers you with the tools, algorithms, and project-based experience to turn raw data into smart business decisions and intelligent systems.
Technology Trends:
- Predictive analytics, chatbots, recommendation systems
- Generative AI, LLMs, and reinforcement learning
- AI-powered automation in healthcare, finance, and retail
- Duration:
- 240 Hours (One Year)
- Mode:
- (Offline + Online + Projects)
- Modules:
- 6 (Each of 40 Hours)
- Includes:
- Live Projects, Tools Training, Mentorship, Placement Support
Modules Covered
Power BI & Excel
- Tool
- Microsoft Excel, Power BI
- Project
- Sales dashboard for a retail brand
- Outcome
- Learn data cleaning, visualization, DAX, and dashboarding for analytics roles
- Careers
- BI Analyst, Data Analyst
Python & Machine Learning
- Tools
- Python, Jupyter Notebook, Scikit-learn
- Project
- Predictive modeling using customer data
- Outcome
- Master Python basics, NumPy, Matplotlib, and ML algorithms like regression and classification
- Careers
- Data Scientist, ML Developer
Introduction to AI
- Tools
- Python, NLTK, Prolog
- Project
- Build an NLP-based chatbot
- Outcome
- Understand search algorithms, logic representation, and AI problem-solving
- Careers
- AI Researcher, NLP Engineer
Deep Learning
- Tools
- TensorFlow, PyTorch
- Project
- Deep learning model for image classification
- Outcome
- Work with CNNs, RNNs, and neural network architectures for advanced AI tasks
- Careers
- Deep Learning Engineer
ML in Business & Engineering
- Tools
- Scikit-learn, TensorFlow
- Project
- Predictive maintenance system using sensor data
- Outcome
- Apply ML for forecasting, optimization, and automation in business/engineering settings
- Careers
- ML Engineer, Process Analyst
AI for Product Management
- Tools
- AI Analytics Platforms, A/B Testing Tools
- Project
- Build a data-backed roadmap for a mobile app
- Outcome
- Learn how AI integrates into product lifecycle, market strategy, and feature prioritization
- Careers
- AI Product Manager, Business Analyst
UI/UX Design
- TOOLS
- Figma, Adobe XD, Balsamiq, Miro
- Outcomes
- Design an app prototype for a local business
- CAREER ROLES
- UI/UX Designer, Interaction Designer
Mini Project
Learn wireframing, user flow, and usability testing
Front-End Development
- TOOLS
- HTML5, CSS3, JavaScript, Git, Bootstrap
- Outcomes
- Master responsive design, Git versioning, and DOM scripting
- CAREER ROLES
- Front-End Developer, UI Engineer
Mini Project
Build a responsive e-commerce website
Back-End Development
- TOOLS
- Node.js, Express.js, PostgreSQL, MongoDB
- LEARNING OUTCOMES
- Create REST APIs, manage databases, and implement server logic
- CAREER ROLES
- Back-End Developer, API Developer
Mini Project
Blogging platform with login authentication
Database Management
- TOOLS
- MySQL, PostgreSQL, MongoDB
- LEARNING OUTCOMES
- Understand schema design, queries, triggers, and stored procedures
- CAREER ROLES
- Database Administrator, SQL Developer
Mini Project
Design a student record management system
Deployment & DevOps
- TOOLS
- Docker, Jenkins, AWS/GCP
- LEARNING OUTCOMES
- Learn containerization, server hosting, and cloud monitoring
- CAREER ROLES
- DevOps Engineer, Cloud Engineer
Mini Project
Deploy a web application on cloud with CI/CD pipeline
Cybersecurity Essentials
- TOOLS
- Kali Linux, OWASP ZAP, Nmap
- LEARNING OUTCOMES
- Understand security testing, threats, and ethical hacking basics
- CAREER ROLES
- Cybersecurity Analyst, Penetration Tester
Mini Project
Perform a vulnerability assessment on a test website
Program Objectives
- To master tools and languages like Python, Power BI, TensorFlow, Scikit-learn, Prolog, NLTK, and more
- To understand core AI/ML principles, business applications, and intelligent product design
- To work on real-world datasets and use cases through projects and assignments
- To build strong portfolios that demonstrate skills in analytics, deep learning, and AI product strategy
Learning Methodology
One Week Training + Three Week Project per Module
Hybrid Learning Model: Live classes + self-paced assignments
Live Industry Projects: Solve practical problems with real datasets
Mentorship: Personalized guidance by AI/ML experts and data scientists
Soft Skills & Interview Training: Resume building, mock interviews, GitHub/portfolio reviews
Why Choose Us?
- Project-Based Learning with real GitHub portfolios
- Mentorship from senior developers and startup founders
- Hands-on experience with modern tools & frameworks
- Interview preparation and placement support
Future Opportunities
AI-ML is one of the fastest-growing fields, with applications spanning across autonomous systems, customer insights, fraud detection, and industrial automation.
- India's AI market is projected to reach $17 billion by 2027, growing at a CAGR of 25–35%
- AI/ML hiring in India surged 37% YoY in May 2024, and overall, AI jobs grew by 42% over two years.
- Yet, talent supply lags: there's only 1 qualified GenAI engineer for every 10 open roles
Placement Prospects
- Giants like Databricks plan to hire 750+ engineers in India via their Bengaluru R&D hub, investing $250 million in AI expansion.
- While demand is booming, supply falls short—only 46% of graduates are AI ML employable, even as core employability declines to 42.6%
- Roles with tech giants (Google, Amazon, Microsoft), startups, and R&D labs
- Popular job titles: Data Scientist, ML Engineer, AI Researcher
- Salary range: ₹6–20+ LPA depending on skill and specialization
Your future self will thank “you” for taking this step.”
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