Master pandas and NumPy for data manipulation and analysis. Learn DataFrames, Series, array operations, data cleaning, and efficient numerical computing in Python.
Introduction to Python programming for data analysis. Learn pandas, numpy, and visualization libraries for data science.
Do you want to master NumPy and unlock your potential in data science? This course is your comprehensive, hands-on introduction to the foundational library of modern Python computing!NumPy is the absolute core building block for essential data science and machine learning libraries like Pandas, Scikit-learn, and PyTorch. By mastering it, you gain the technical edge needed for advanced topics like linear algebra, image processing, and fast numerical computations. If you want to start a career in Data Science or understand the engine behind Machine Learning in Python, this course is for you.What You'll Master in this Hands-On Python Course:This course will teach you everything you need to professionally use NumPy for scientific computing. We start with the basics and rapidly move into advanced techniques crucial for complex data science tasks.Foundation: Introduction to NumPy arrays, N-dimensional arrays, and the fundamental concepts of vectors and matrices.Data Analysis Tools: Leverage Universal Functions (ufuncs), Randomness, and Statistics to analyze and explore data efficiently in Python.Linear Algebra for ML: Master Basic and Advanced Linear Algebra operations, which are the backbone of all Machine Learning algorithms.Advanced Techniques: Understand Broadcasting and Advanced Indexing to write fast, memory-efficient Python code.Real-World Scientif
A practical guide to data wrangling using Python and the pandas library. The article covers reading data, accessing columns and rows, handling missing values, and data normalization, which are crucial steps for preparing data for analysis and machine learning.
A hands-on learning path that teaches data cleaning and preprocessing in Python, covering topics from basic data cleaning tasks to more advanced techniques for handling messy data.
A project-based course that teaches practical techniques for cleaning messy data in Microsoft Excel, including data manipulation and transformation.
This chapter from an online book on Data Science with Python focuses on data wrangling operations using the Pandas library. It covers hierarchical indexing, combining datasets through merging, joining, and concatenating, and reshaping data with pivot and melt functions.
In today's data-driven world, the ability to harness and interpret data is not just a valuable skill but a crucial advantage. Whether you're an aspiring data scientist, a seasoned professional looking to expand your skill set, or an entrepreneur aiming to leverage data for strategic decisions, our comprehensive course on data science offers a transformative learning experience.Course OverviewOur course begins with a foundational exploration of data science, introducing you to its principles and importance in various industries. You'll delve into the distinctions between data science, data engineering, and data analysis, gaining a clear understanding of their respective roles and applications. Through real-world case studies and examples, you'll discover how data science drives innovation and impacts decision-making processes across different sectors.Essential Tools and TechnologiesTo equip you with the tools needed for effective data analysis, the course covers essential programming languages such as Python . Whether you're manipulating data with Pandas, performing numerical operations with NumPy, or creating insightful visualizations with Matplotlib and Seaborn, you'll develop a versatile skill set that forms the backbone of data science projects.Practical Skills DevelopmentA significant focus of the course is hands-on learning. You'll gain practical experience in gathering, cleaning, and analyzing data from diverse sources. You'll hone your ability to transform raw data into actionable insights that drive business decisions.Environment Setup and Best PracticesNavigating the data science environment can be daunting, especially for beginners. That's why we guide you through the setup of Python and Jupyter Notebook on both Windows and macOS, ensuring you're equipped with the right tools from the start. You'll learn to create and manage virtual environments, enhancing your ability to work efficiently and maintain project dependencies.Data
In today's data-driven world, the ability to harness and interpret data is not just a valuable skill but a crucial advantage. Whether you're an aspiring data scientist, a seasoned professional looking to expand your skill set, or an entrepreneur aiming to leverage data for strategic decisions, our comprehensive course on data science offers a transformative learning experience.Course OverviewOur course begins with a foundational exploration of data science, introducing you to its principles and importance in various industries. You'll delve into the distinctions between data science, data engineering, and data analysis, gaining a clear understanding of their respective roles and applications. Through real-world case studies and examples, you'll discover how data science drives innovation and impacts decision-making processes across different sectors.Essential Tools and TechnologiesTo equip you with the tools needed for effective data analysis, the course covers essential programming languages such as Python and R. Whether you're manipulating data with Pandas, performing numerical operations with NumPy, or creating insightful visualizations with Matplotlib and Seaborn, you'll develop a versatile skill set that forms the backbone of data science projects.Practical Skills DevelopmentA significant focus of the course is hands-on learning. From introductory SQL for data querying to advanced techniques in web scraping for data retrieval, you'll gain practical experience in gathering, cleaning, and analyzing data from diverse sources. Through interactive exercises and projects, you'll hone your ability to transform raw data into actionable insights that drive business decisions.Environment Setup and Best PracticesNavigating the data science environment can be daunting, especially for beginners. That's why we guide you through the setup of Python and Jupyter Notebook on both Windows and macOS, ensuring you're equipped with the right tools from the start. You'll l
Unlock the power of interactive data science with Interactive Data Science in Python — a comprehensive, beginner-friendly course designed to take you from novice to confident practitioner. We begin by exploring Shiny, the dynamic and popular web app framework for Python, where you'll learn how to build interactive dashboards, responsive data visualizations, and user-friendly interfaces using the classic Shiny library. Once you’ve gained solid skills, you’ll transition smoothly to Shiny Express, a modern, more streamlined toolkit that accelerates app development while maintaining full flexibility.Alongside Shiny, you’ll dive deep into essential Python data science libraries like Pandas, Seaborn, and Matplotlib. You’ll master how to clean, analyze, visualize, and explore complex datasets with clarity and precision, empowering you to uncover patterns and tell compelling stories with data.This course also introduces PyTorch basics from scratch — perfect for beginners eager to explore deep learning and neural networks. You’ll grasp fundamental machine learning concepts and get hands-on experience building your own models, preparing you to confidently tackle more advanced AI projects.Throughout the course, you’ll engage with practical coding exercises, real-world datasets, and projects focused on creating interactive applications that captivate users and dynamically reveal insights. Whether you aspire to be a data scientist, analyst, or developer, this course will equip you with the skills and confidence to build powerful data-driven applications and understand foundational deep learning techniques in Python.Jump in today and bring your data to life with interactive, intelligent applications!
Learn Python for Data Analysis and Visualization
This course equips Python developers with the foundational NumPy skills essential for data science and machine learning. You’ll move beyond basic lists to master high-performance ndarrays: creating, reshaping, indexing, slicing, and performing vectorized operations — all without slow loops. Learn key concepts like shape, dtype, axis, and the powerful broadcasting mechanism that makes NumPy so efficient. Through hands-on examples (e.g., analyzing grades or sensor data), you’ll gain confidence in mathematical computation, array manipulation, and data preparation. By the end, you’ll seamlessly integrate NumPy with Pandas and scikit-learn — setting the stage for real-world DS/ML workflows. No advanced math needed — just core Python (variables, loops, functions) and a willingness to practice. Includes setup guides, Jupyter notebooks, and practical exercises. Whether you're a student, career-switcher, or self-learner, this is your essential first step into the data ecosystem.هذه الدورة مُعدَّة لمُطوري بايثون لإتقان NumPy — حجر الأساس في علم البيانات وتعلم الآلة. ستنتقل من استخدام القوائم العادية إلى إنشاء ومعالجة المصفوفات عالية الأداء (ndarray) بثقة: التشكيل (reshape)، الفهرسة الذكية، العمليات المتجهية (بدون حلقات بطيئة)، وفهم الخصائص مثل shape وdtype وaxis. ستتعلم مفهوم الـ Broadcasting السحري الذي يجعل العمليات سريعة ومرنة، عبر أمثلة واقعية (مثل تحليل درجات طلاب أو بيانات مناخية). كما ستُجهّز البيانات للانتقال السلس إلى أدوات مثل Pandas و scikit-learn. لا تحتاج إلى خلفية رياضية متقدمة — يكفي أن تعرف أساسيات بايثون (متغيرات، حلقات، دوال). تشمل الدورة شرحًا خطوة بخطوة، دفاتر جوبيتر جاهزة، وتمارين تطبيقية. سواء كنت طالبًا أو تُغيّر مسارك المهني، فهذه الدورة هي بداية رحلتك العملية في عالم البيانات.
Learn Python for Data Science and Machine Learning Bootcamp
One of the most essential aspects of Data Science or Machine Learning is Data Cleaning. In order to get the most out of the data, your data must be clean as uncleaned data can make it harder for you to train ML models. In regard to ML & Data Science, data cleaning generally filters & modifies your data making it easier for you to explore, understand and model.A good statistician or a researcher must spend at least 90% of his/her time on collecting or cleaning data for developing a hypothesis and remaining 10% on the actual manipulation of the data for analyzing or deriving the results. Despite these facts, data cleaning is not commonly discussed or taught in detail in most of the data science or ML courses. With the rise of big data & ML, now data cleaning has also become equally important.Why should you learn Data Cleaning?Improve decision makingImprove the efficiencyIncrease productivityRemove the errors and inconsistencies from the datasetIdentifying missing valuesRemove duplicationWhy should you take this course?Data Cleaning is an essential part of Data Science & AI, and it has become an equally important skill for a programmer. It’s true that you will find hundreds of online tutorials on Data Science and Artificial Intelligence but only a few of them cover data cleaning or just give the basic overview. This online guide for data cleaning includes numerous sections having over 5 hours of video which are enough to teach anyone about all its concepts from the very beginning. Enroll in this course now to learn all the concepts of Data Cleaning. This course teaches you everything including the basics of Data Cleaning, Data Reading, merging or splitting datasets, different visualization tools, locate or handling missing/absurd values and hands-on sessions whe
This specialization provides a deep dive into data wrangling techniques using Python, including data collection, assessment, and cleaning, as well as handling missing values.
Learn The Data Science Course 2025: Complete Data Science Bootcamp
Learn Complete Python Pandas Data Science Course
Hello there,Welcome to Python Numpy: Machine Learning & Data Science CoursePython numpy, Numpy python, python numpy: machine learning & data science, python numpy, machine learning data science course, machine learning python, data science, python, oak academy, machine learning, python machine learning, python data science, numpy course, data science courseLearn Numpy and get comfortable with Python Numpy in order to start into Data Science and Machine Learning OAK Academy offers highly-rated data science courses that will help you learn how to visualize and respond to new data, as well as develop innovative new technologies Whether you’re interested in machine learning, data mining, or data analysis, Udemy has a course for you Data science is everywhere Better data science practices are allowing corporations to cut unnecessary costs, automate computing, and analyze markets Essentially, data science is the key to getting ahead in a competitive global climate Python Numpy, Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels Whether you work in machine learning or finance, or are pursuing a career in web development or data science, Python is one of the most important skills you can learn Python's simple syntax is especially suited for desktop, web, and business applications Python's design philosophy emphasizes readability and usability Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization The core programming language is quite small and the standard library is also large In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasksAre you re
This course provides a practical guide to data cleaning in R, covering everything from common data problems to techniques for tidying data.
Hello there,Machine learning python, python, machine learning, Django, ethical hacking, python bootcamp, data analysis, machine learning python, python for beginners, data science, machine learning, django:Welcome to the “Python: Machine Learning, Deep Learning, Pandas, Matplotlib” course. Python, Machine Learning, Deep Learning, Pandas, Seaborn, Matplotlib, Geoplotlib, NumPy, Data Analysis, TensorflowPython instructors on Udemy specialize in everything from software development to data analysis and are known for their effective, friendly instruction for students of all levels.Machine learning isn’t just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries and new problems. Whether you’re a marketer, video game designer, or programmer, this course is here to help you apply machine learning to your work.In this course, we will learn what is Deep Learning and how does it work.This course has suitable for everybody who is interested in Machine Learning and Deep Learning concepts in Data Science.First of all, in this course, we will learn some fundamental stuff of Python and the Numpy library. These are our first steps in our Deep Learning journey. After then we take a little trip to Machine Learning Python history. Then we will arrive at our next stop. Machine Learning in Python Programming. Here we learn the machine learning concepts, machine learning a-z workflow, models and algorithms, and what is neural network concept. After then we arrive at our next stop. Artificial Neural network. And now our journey becomes an adventure. In this adventure we'll enter the Keras world then we exit the Tensorflow world. Then we'll try to under
This tutorial explains the process of gathering, collecting, and transforming raw data into another format for better understanding and analysis using the Pandas framework in Python. It covers data exploration, handling missing values, reshaping data, and filtering.
This course provides a comprehensive introduction to data wrangling with the Pandas library in Python, covering essential data cleaning and transformation techniques.
In today's data-driven world, the ability to harness and interpret data is not just a valuable skill but a crucial advantage. Whether you're an aspiring data scientist, a seasoned professional looking to expand your skill set, or an entrepreneur aiming to leverage data for strategic decisions, our comprehensive course on data science offers a transformative learning experience.Course OverviewOur course begins with a foundational exploration of data science, introducing you to its principles and importance in various industries. You'll delve into the distinctions between data science, data engineering, and data analysis, gaining a clear understanding of their respective roles and applications. Through real-world case studies and examples, you'll discover how data science drives innovation and impacts decision-making processes across different sectors.Essential Tools and TechnologiesTo equip you with the tools needed for effective data analysis, the course covers essential programming languages such as Python . Whether you're manipulating data with Pandas, performing numerical operations with NumPy, or creating insightful visualizations with Matplotlib and Seaborn, you'll develop a versatile skill set that forms the backbone of data science projects.Practical Skills DevelopmentA significant focus of the course is hands-on learning. You'll gain practical experience in gathering, cleaning, and analyzing data from diverse sources. Through interactive exercises and projects, you'll hone your ability to transform raw data into actionable insights that drive business decisions.Environment Setup and Best PracticesNavigating the data science environment can be daunting, especially for beginners. That's why we guide you through the setup of Python and Jupyter Notebook on both Windows and macOS, ensuring you're equipped with the right tools from the start. You'll learn to create and manage virtual environments, enhancing your ability to work efficiently and mai
Unlock the Power of Data Science SkillsIn today's data-driven world, the ability to harness and interpret data is not just a valuable skill but a crucial advantage. Whether you're an aspiring data scientist, a seasoned professional looking to expand your skill set, or an entrepreneur aiming to leverage data for strategic decisions, our comprehensive course on data science offers a transformative learning experience.Course OverviewOur course begins with a foundational exploration of data science, introducing you to its principles and importance in various industries. You'll delve into the distinctions between data science, data engineering, and data analysis, gaining a clear understanding of their respective roles and applications. Through real-world case studies and examples, you'll discover how data science drives innovation and impacts decision-making processes across different sectors.Essential Tools and TechnologiesTo equip you with the tools needed for effective data analysis, the course covers essential programming languages such as Python and R. Whether you're manipulating data with Pandas, performing numerical operations with NumPy, or creating insightful visualizations with Matplotlib and Seaborn, you'll develop a versatile skill set that forms the backbone of data science projects.Practical Skills DevelopmentA significant focus of the course is hands-on learning. You'll gain practical experience in gathering, cleaning, and analyzing data from diverse sources. You'll hone your ability to transform raw data into actionable insights that drive business decisions.Environment Setup and Best PracticesNavigating the data science environment can be daunting, especially for beginners. That's why we guide you through the setup of Python and Jupyter Notebook on both Windows and macOS, ensuring you're equipped with the right tools from the start. You'll learn to create and manage virtual environments, enhancing your abili
Hello there,Welcome to the " Machine Learning & Data Science with Python, Kaggle & Pandas " CourseMachine Learning A-Z course from zero with Python, Kaggle, Pandas and Numpy for data analysis with hands-on examplesMachine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.You can develop the foundational skills you need to advance to building neural networks and creating more complex functions through the Python and R programming languages. Machine learning helps you stay ahead of new trends, technologies, and applications in this field.Machine learning is being applied to virtually every field today. That includes medical diagnoses, facial recognition, weather forecasts, image processing, and more. In any situation in which pattern recognition, prediction, and analysis are critical, machine learning can be of use. Machine learning is often a disruptive technology when applied to new industries and niches. Machine learning engineers can find new ways to apply machine learning technology to optimize and automate existing processes. With the right data, you can use machine learning technology to identify extremely complex patterns and yield highly accurate predictions.It’s hard to imagine our lives without machine learning. Predictive texting, email filtering, and virtual personal assistants like Amazon’s Alexa and the iPhone’s Siri, are all technologies that function based on machine learning algorithms and mathematical models. Python, machine learning, django, python programming, machine learning python, python for beginners, data science. Kaggle, statistics, r, python data science, deep learning, python programming, django, machine learning a-z, data scientist, python for data sciencePandas is an open source Python package that is most widely used for d
A comprehensive, free video course on YouTube that covers the essential Python libraries for data analysis and visualization, perfect for learning EDA.
This course provides a comprehensive overview of data cleaning techniques in Python, from identifying and handling missing data to dealing with inconsistent data formats.
This course teaches the fundamentals of data wrangling and cleaning using Python and the Pandas library, essential skills for any data scientist.
A talk from the Spark/AI Summit about the Hopsworks Feature Store and its integration with Databricks. It explains how the feature store centralizes features for easier discovery, governance, and reuse.
Learn IBM Data Science Professional Certificate
Explore all AI tools and technologies.
Explore courses by AI concepts and disciplines.
Browse courses organized by learning category.
Browse courses from Coursera, edX, Udemy, and more.
Search and filter across all AI and ML courses.
Find courses for your career path — data scientist, ML engineer, AI researcher, and more.
Start your AI journey with beginner-friendly courses.