Overview
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.
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.
No prior programming or data science experience is required., A basic understanding of high school math is helpful, but all concepts are taught from scratch with hands-on examples.
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.
Temotec AI Learning
Hello, I'm a Passionate Developer, Data Scientist and Data Engineer with over 7 years of experience in the field. I have worked with some of the top tech companies around the world.
My expertise lies in Machine Learning, Big Data Processing, Data Mining, and Cloud Computing. I have a deep understanding of various data structures and algorithms, as well as proficiency in programming languages such as Python, R, and SQL.
Throughout my career, I've helped businesses make sense of their data, develop data-driven strategies, and drive decision-making processes. I've also published several research papers in top-tier journals and have been a speaker at numerous international conferences.
As an instructor on Udemy, my goal is to share my knowledge and experience with you, whether you're just starting out or looking to advance your skills. My courses are designed to be practical and engaging, with real-world examples and hands-on exercises.
Join me on this journey to explore the fascinating world of Data Science and Data Engineering. Let's unlock the power of data together!