AI/ML & Data Science Programming Foundations. Hands-on Projects, Deployment + Career Launch
About Course
This industry-focused AI/ML & Data Science course is designed for college students (BCA, MCA, B.Tech, and graduates), freshers, and career switchers who want to build a strong foundation in AI & ML, work on real-world projects, and launch a career in data science.
With expert mentorship, hands-on projects, real-world deployment experience, and career guidance, this course will equip you with the right skills to land a job, internship, or freelance projects in AI/ML.
🚀 What You Will Learn:
✅ Foundations of AI & ML – Mathematics, Python, Data Structures & Algorithms
✅ Data Science & ML Programming – Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch
✅ Real-World AI/ML Projects – End-to-end projects from Data Preprocessing to Model Deployment
✅ Cloud & Deployment – AWS, Azure, Google Cloud, Streamlit, Flask, FastAPI
✅ Internship Readiness – Resume Building, Portfolio Projects, GitHub & Kaggle Profiling
✅ Career Roadmap – Job Interviews, Mock Interviews, and LinkedIn Optimization
🎯 Who Is This Course For?
💡 Students & Freshers – Looking for an internship or first job in AI/ML
💡 Career Switchers – Moving from non-tech roles to AI/Data Science
💡 Software Engineers – Upskilling to get high-paying AI/ML jobs
💡 Entrepreneurs & Freelancers – Want to build AI-powered applications
🛠️ Key Features:
✅ 100% Hands-on Learning – Learn by doing, not just theory
✅ Project-Based Approach – Build 5+ real-world AI/ML projects
✅ Internship & Job Support – Resume reviews, mock interviews & job referrals
✅ 1-on-1 Mentorship – Personalized guidance for career growth
✅ Certificate of Completion – Showcase your AI/ML expertise
💼 Career Outcomes:
✔ AI/ML Engineer
✔ Data Scientist
✔ Deep Learning Engineer
✔ Data Analyst
✔ ML Ops Engineer
By the end of this course, you’ll have the skills, projects, and confidence to secure an internship, job, or freelance opportunity in AI/ML.
🚀 Ready to start your AI/ML journey? Join now & take the first step toward a high-paying career in AI & Data Science!
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Course Content
Module 1: Introduction to AI/ML & Essential Mathematics – Build Rock-Solid Fundamentals
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AI vs ML vs Data Science – Industry Use Cases
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Basic Statistics & Probability – (Applied to AI/ML)
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Linear Algebra (Vectors, Matrices, Eigenvalues) – (Applied to AI/ML)
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Calculus (Derivatives, Gradients, Optimization) – (Applied to AI/ML)
Module 2: Python for Data Science & ML
Module 3: Exploratory Data Analysis (EDA) & Feature Engineering
Module 4: Machine Learning Fundamentals
Module 5: Advanced Machine Learning
Module 6: Deep Learning with Neural Networks
Module 7: CNNs & NLP for AI Applications
Module 8: Model Deployment & MLOps
Module 9: Hands-on Projects & Case Studies
Module 10: Internship Readiness & Resume Building
Module 11: Mock Interviews & Industry Networking
Module 12: Final Capstone Project & Career Launch
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