Build & Deploy 10+ Real-World Data Science & GenAI Projects
Published 3/2026
Created by DS with Bappy
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 163 Lectures ( 36h 29m ) | Size: 31.7 GB
Build, Train & Deploy End-to-End AI Systems using ML, Big Data, DL, CV, NLP & Gen AI with Real-World Projects
What you'll learn
✓ Complete Lifecycle: Master the full Data Science pipeline-from data ingestion and validation to model evaluation and deployment.
✓ Real-World Deployment: Learn to deploy models to the cloud using AWS, GCP and Azure with automated CI/CD pipelines.
✓ Production Tools: Get hands-on experience with industry-standard tools like Docker, MLOps (MLflow, DVC, Sagemeker,Kubeflow,Kubernetes, BentoML), and FastAPI.
✓ Modular Coding: Transition from messy notebooks to professional, modular Python code structures used in top tech companies.
✓ Data Drift & Monitoring: Understand how to detect data drift and maintain model performance after deployment.
✓ ML, DL, CV & NLP: Build advanced projects from all different domains.
Requirements
● Basic Python Knowledge: You should be comfortable with Python basics (loops, functions, and basic data types).
● Fundamental Math: A high-school level understanding of statistics and linear algebra is helpful but not mandatory.
● Environment: A computer (Windows, Mac, or Linux) with an internet connection. We will set up all tools (VS Code, Python, Git) together.
● No Prior Data Science Experience Needed: I will guide you through the "Why" and "How" of every algorithm we use.
Description
In today's competitive tech landscape, simply learning theory is not enough-you need real-world experience. This course is designed to help you move beyond tutorials and actually build and deploy production-ready Data Science and Generative AI applications.
In this hands-on course, you will work on 10+ real-world projects that simulate industry use cases. You will learn how to take an idea from scratch and turn it into a fully functional, deployed application. Each project is carefully designed to strengthen your understanding of core concepts while also giving you practical exposure to modern tools and workflows.
We will cover a wide range of topics, including Machine Learning, Big Data, Deep Learning, Computer Vision, Natural Language Processing (NLP), and Generative AI. You will also learn how to integrate APIs, work with real datasets, optimize models, and deploy your applications using modern platforms.
By the end of this course, you will
• Build strong, portfolio-ready projects
• Gain confidence in solving real-world problems
• Understand end-to-end project pipelines
• Learn deployment strategies used in the industry
• Be prepared for Data Science and AI job roles
This course is perfect for students, aspiring data scientists, developers, and professionals who want to gain practical, job-ready skills. Whether you're looking to enhance your portfolio or break into the AI industry, this course will give you everything you need to stand out.
Who this course is for
■ Aspiring Data Scientists: Beginners who want to move beyond basic tutorials and build a job-ready portfolio.
■ Software Engineers: Developers looking to transition into the AI/ML space by applying their existing coding skills to data projects.
■ Students & Graduates: Anyone looking to land an internship or entry-level role by showcasing live, deployed projects to recruiters.
■ AI Engineer: Professionals who want to level up their skills by learning how to automate and deploy their insights as web applications.
Homepage
https://anonymz.com/?https://www.udemy.com/course/build-deploy-10-real-world-data-science-genai-projects
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