Name: Data Science & AI Mastery: From Basics to Deployment
Availability: InStock

What You'll Learn

Clean, analyze, and prepare data for real-world machine learning and AI applications.
Build and evaluate machine learning models for regression, classification, clustering, and recommendation systems.
Apply deep learning techniques such as neural networks, CNNs, RNNs, and generative AI for advanced use cases.
Work confidently with Python, Pandas, NumPy, Scikit-Learn, TensorFlow, and PyTorch to solve end-to-end problems
Perform feature engineering, model optimization, and hyperparameter tuning to improve accuracy
Deploy models into production using APIs (FastAPI, Flask), Docker, and Streamlit dashboards.
Understand the basics of MLOps, including model monitoring, performance tracking, and drift detection.
Tackle real-world projects and a capstone, gaining the confidence to showcase a complete portfolio to employers.
Translate technical outputs into business insights and decision-making strategies.
Prepare for career roles like Data Scientist, Machine Learning Engineer, or AI Specialist.

Requirements

Basic computer literacy – comfort with installing software, navigating files, and using online tools.
Familiarity with mathematics fundamentals – especially algebra, probability, and basic statistics (no advanced math required).
Beginner-level Python knowledge – understanding variables, loops, functions, and simple data structures.
A computer with Windows, macOS, or Linux and internet connection to run tools and complete labs.
Curiosity, persistence, and a willingness to learn by doing—no prior machine learning or AI experience required.

Beginners in Data Science & AI who want a structured, step-by-step path to mastery.
Students and recent graduates looking to gain practical skills and build a strong project portfolio.
Professionals in IT, software engineering, or business analytics who want to transition into data science and machine learning roles.
Working data analysts who want to upgrade from basic analytics to machine learning and AI applications.
Career changers from non-technical backgrounds who are motivated to learn programming and data-driven problem solving
Entrepreneurs and innovators who want to apply AI techniques to real-world challenges and startup ideas.
Anyone passionate about hands-on learning, real-world case studies, and building job-ready skills in a fast-growing field.

Bridging knowledge to industry with Data & AI education

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34,855 Students

14 Courses

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