Mastering Data Science & AI with Python & Real-World Project | Udemy
English | Size: 10.29 GB
Genre: eLearning[/center]

A complete hands-on Python, Machine Learning, LLM-powered AI apps featuring 9 real-world projects, Streamlit & Ollama.

What you'll learn
Learn to code in Python and apply core libraries like NumPy and Pandas for data manipulation and analysis.
Master essential statistics and data visualization techniques to extract actionable insights from data.
Understand and implement key machine learning algorithms including regression, classification, clustering, and dimensionality reduction.
Build and deploy real-world AI and machine learning projects using tools like Streamlit, and Ollama-powered LLMs.

Unlock the full potential of data science and artificial intelligence with "Mastering Data Science & AI with Python"-a comprehensive, beginner-to-advanced course designed to transform you into a job-ready data scientist and AI developer. Whether you're just starting your coding journey or looking to upskill and build real-world AI-powered applications, this course covers everything you need in one complete package.

We begin with the fundamentals of Python, ensuring you're well-equipped with programming basics and critical libraries like NumPy and Pandas. You'll quickly progress to manipulating and analyzing data efficiently, including accessing, cleaning, and filtering DataFrames. Learn how to visualize your insights with powerful charts and graphs that bring your data to life.

From there, you'll dive deep into statistics for data science, the cornerstone for understanding machine learning. You'll master core statistical concepts essential for model development and evaluation. The machine learning section then takes you through supervised and unsupervised learning-covering regression, binary and multiclass classification, clustering algorithms, and dimensionality reduction techniques like t-SNE and PCA.

Hands-on practice is the heart of this course. You'll complete 9 end-to-end projects that simulate real industry scenarios:

Automate business workflows with Pandas

Analyze large datasets with Google Apps

Build a movie recommendation engine using Non-negative Matrix Factorization

Develop predictive models and evaluate them using advanced techniques

Build and deploy a credit risk prediction app with XGBoost and Streamlit

Create LLM-powered AI apps using Ollama, LangChain, and Streamlit-no cloud required

Implement local Python libraries for AI interactions

What truly sets this course apart is its focus on local LLMs and AI automation tools. You'll explore cutting-edge frameworks like Ollama, interact with models through Web UI, LM Studio, and even build your own AI Code Assistant and RAG-based AI Research App-equipping you with the skills to develop, test, and deploy modern AI systems without relying on expensive APIs or cloud services.

All modules are crafted with a blend of theory, code-alongs, and practical exercises. You'll walk away not only with technical knowledge but also a portfolio of working applications that showcase your expertise in Python programming, machine learning, and AI.

By the end of this course, you will be able to:

Code in Python with confidence

Analyze, visualize, and model data effectively

Understand and implement ML algorithms from scratch

Build real-world projects that demonstrate your skills

Develop and deploy AI apps using local LLMs and tools like Ollama and Streamlit

This course is ideal for aspiring data scientists, developers, and AI enthusiasts eager to build practical, high-impact solutions. If you're looking to transition into tech, upgrade your skills, or break into AI development, this is the only course you'll need.

Who this course is for:
This course is ideal for aspiring data scientists, developers.
AI enthusiasts who want to gain hands-on experience building real-world projects.
It's also perfect for beginners looking to break into tech, professionals seeking to expand into AI.
Students eager to learn Python, data science, and local LLM development from the ground up.

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