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- Email: hr@hypertechglobaltechnologies.com
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Instructor: Team HyperTech
Programming Basics: Python, JavaScript
Software Engineering Principles
Git/GitHub & Agile Methodologies
Introduction to Databases (SQL/NoSQL)
Math for AI (Linear Algebra, Probability, Statistics)
Object-Oriented Programming (OOP)
Full-Stack Development Basics (HTML, CSS, JS, Node.js/React)
API Development & Integration
Database Design & Optimization
Cloud Basics (AWS/GCP/Azure)
Python for AI (NumPy, Pandas, Matplotlib)
Machine Learning Fundamentals (Regression, Classification, Clustering)
Neural Networks & Deep Learning Basics (TensorFlow, PyTorch)
Data Preprocessing & Feature Engineering
Hands-on ML Projects (Predictive Models, Recommendation Engines)
Natural Language Processing (NLP)
Computer Vision (CV) Applications
Generative AI (LLMs, Transformers, GANs)
AI for Software Development (GitHub Copilot, Code Assistants)
Capstone 1: AI-powered Web App
AI in Cloud & DevOps (MLOps, CI/CD pipelines for AI)
Scalable Software Systems with AI Integration
AI Ethics, Bias, and Responsible AI Practices
Enterprise AI Case Studies
Capstone 2: Enterprise AI Solution
Specializations: Choose Data Science, AI Engineering, or AI Product Development
Interview Prep: DSA, System Design, AI problem-solving
Portfolio Building (GitHub, LinkedIn projects, blogs)
Mock Interviews with Industry Mentors
Final Capstone: AI-driven Product Launch
Full-stack developer skills with AI integration
Proficiency in ML, NLP, CV, and Generative AI
Cloud & DevOps practices for AI systems (MLOps)
3 Capstone projects + strong portfolio
Industry readiness for roles like AI Engineer, Software Developer – AI, ML Developer, or Data Scientist
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🗓️ Month-Wise Learning Plan (9 Months) 🧩 Month 1: Programming Foundations & Problem Solving ▪ Core programming using Python / Java (choice-based) ▪ Variables, loops, functions, recursion ▪ Time & space complexity basics ▪ Introduction to problem-solving patterns ▪ Hands-on coding sessions + daily practice 📌 Outcome: Strong logical thinking & coding confidence 🧠 Month 2: Data Structures – Core ▪ Arrays, Strings, Hashing ▪ Stacks, Queues, Linked Lists ▪ Sliding window & two-pointer techniques ▪ Pattern-based problem solving ▪ LeetCode / InterviewBit-style problems 📌 Outcome: Crack easy–medium coding rounds confidently 🌲 Month 3: Data Structures – Advanced ▪ Trees, Binary Search Trees ▪ Heaps & Priority Queues ▪ Graphs (BFS, DFS, shortest path) ▪ Recursion & Backtracking ▪ Dynamic Programming (intro to advanced) 📌 Outcome: Handle complex interview-level problems 🧱 Month 4: System Design – Foundations ▪ How large-scale systems work ▪ Load balancing, caching, databases ▪ CAP theorem, consistency models ▪ REST APIs, monolith vs microservices ▪ Low-level design (LLD) basics 📌 Design Case Studies: ✔ URL Shortener ✔ Notification System ✔ File Storage System 🏗️ Month 5: System Design – Advanced ▪ High-level design (HLD) ▪ Scalable backend architectures ▪ Database sharding & replication ▪ Message queues (Kafka / RabbitMQ) ▪ Designing for millions of users 📌 Design Case Studies: ✔ E-commerce platform (Amazon-style) ✔ Food delivery system (Blinkit-style) ✔ Fintech transaction system ☁️ Month 6: Cloud-Native Development ▪ Backend development using Node.js / Python ▪ REST APIs with authentication & authorization ▪ Cloud basics (AWS/GCP/Azure overview) ▪ Deploying applications on cloud ▪ Real-time databases & storage 📌 Project: Deploy a production-ready backend service on cloud 🤖 Month 7: AI-Assisted Software Development ▪ Using AI tools for engineering productivity ▪ Prompt engineering for developers ▪ AI for debugging, refactoring & testing ▪ Intro to ML concepts for engineers ▪ Integrating AI APIs into applications 📌 Project: AI-powered feature inside a real application ⚙️ Month 8: DevOps, MLOps & Production Engineering ▪ CI/CD pipelines (Git, Jenkins/GitHub Actions) ▪ Docker & containerization ▪ Kubernetes basics ▪ Monitoring, logging & alerts ▪ Secure deployments & DevSecOps concepts 📌 Project: End-to-end CI/CD + cloud deployment pipeline 🎓 Month 9: Capstone Projects & Placement Prep ▪ 2–3 industry-grade capstone projects ▪ Mock interviews (DSA + System Design) ▪ Resume & GitHub optimization ▪ Behavioral & HR interview prep ▪ Placement pipeline & referrals 📌 Capstone Examples: ✔ Scalable SaaS backend (Deloitte-style) ✔ AI-driven analytics platform (PwC/KPMG-style) ✔ Cloud-native enterprise system (TCS-style) 🧪 Key Program Highlights ✔ Live instructor-led classes ✔ Daily coding practice & evaluations ✔ Real-world system design projects ✔ AI-integrated development workflow ✔ Cloud deployment & production exposure ✔ Placement-focused learning path 💼 Placement Model Learners pay only 50% fee during the program Remaining 50% payable after placement Complimentary interview preparation Dedicated placement & referral support
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