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This is the Python course that will not only develop your programming skills but will also give you a problem-solving superpower using Python code! In this course, you will develop a thorough understanding of Python, how to program in Python, and how to think computationally. You will learn how to implement object-oriented programming (OOP), how to create Python charts in Matplotlib, and how to work with different IDEs like Spyder and Jupyter. While you're learning, you'll get to practice your skills with fun and challenging exercises like solving the Sierpinski Triangle and the Towers of Hanoi. Finally, your instructor, Giles McMullen-Klein, is a British programmer who went to Oxford University and used Python for his research there. He's motivating, enthusiastic, and truly passionate about Python! Hone your skills with the Python Bootcamp course. Develop a thorough understanding of how to program with Python, and how to think computationally. Try it for free!

Python is one of the most widely-used programming languages among data scientists. This course will show you the technical advantages it has over other programming languages. You will start working with its modules for scientific computing, and you will begin to understand why these functionalities make Python the preferred choice in finance, econometrics, economics, data science, and machine learning. Do you want to learn Python? Try 365 Data Science course Python for Beginners. Learn the basic skills needed to be a Python developer. Try it for free!

Python for Finance is the crossing point where programming in Python blends with financial theory. Together, they give you the know-how to apply that theory into practice and real-life scenarios. In a world where individuals and companies are aiming to become more and more autonomous, your ability to combine programming skills with financial data will allow you to create independent analyses. And that competency will give you an edge over your competitors or in your personal investments. To prepare you for these multi-faceted challenges, this course provides the relevant topics in financial theory and their hands-on application in Python. Do you want to learn Python for Finance? Learn how to combine programming skills with financial data to create outstanding independent analyses. Start now!

Machine Learning in Python builds upon the statistical knowledge you have gained earlier in the program. This course focuses on predictive modeling and enters multidimensional spaces that require an understanding of mathematical methods, transformations, and distributions. The course introduces these concepts as well as complex means of analysis such as clustering, factoring, Bayesian inference, and decision theory while also allowing you to exercise your Python programming skills. Looking for a Machine Learning in Python course? 365 Data Science will prep you for predictive modeling, transformations, and distributions. Try it for free!

Credit risk modeling is the place where data science and fintech meet. It is one of the most important activities conducted in a bank and the one with the most attention since the recession. This course is the only comprehensive credit risk modeling course in Python available right now. It shows the complete credit risk modeling picture, from preprocessing, through the probability of default (PD), loss given default (LGD) and exposure at default (EAD) modeling, and finally finishing off with calculating expected loss (EL). Looking for a Credit Risk Modeling in Python course? Find the only comprehensive credit risk modeling course in Python available right now. Try it for free!

Web Scraping and API Fundamentals in Python offers an introduction to the techniques of data extraction from the web. In this course, you will learn how to use one of the most powerful tools on the Internet - APIs. We will also discuss in depth how to obtain information directly from websites using the BeautifulSoup Python package. There will be a short HTML crash course for those not familiar with it. Finally, we will introduce the Requests-HTML package to extract dynamically generated JavaScript content. Do you want to learn Web Scraping and API Fundamentals in Python? Sign up for the 365 Data Science Program and learn the skills needed to become a Web Scraping pro. Start now!

The Data Visualization course is designed for everyone looking to deepen their understanding of creating meaningful and compelling visualizations. Whether you're coming from a business or data science-related field, knowledge in data visualization is both important and advantageous. That's precisely why this course is centered not in just one, but four different environments: Excel, Tableau, Python, and R. Each section is dedicated to a specific type of chart - bar charts, pie charts, area charts, line charts, and many more. Besides, some lectures specifically explore what to avoid when creating a certain graphic. You can stick with your preferred environment and follow each section. Or you could master all four environments and add indispensable skills to your data visualization toolset. Looking for a Data Visualization course? Learn how to create compelling charts and graphs with Excel, Tableau, Python, and R. Try it for free!

While Python is the leading programming language for data science, SQL is unmatched when it comes to relational database management. Tableau, on the other hand, is a leading business intelligence software, providing tools for quick computations and rich visualizations. This course will show you how to combine these software products to solve real-life business problems. Learn how to use SQL, Tableau, and Python together with a course from 365 Data Science. Learn how to solve real-life business problems. Try it for free!

Customer Analytics in Python is where marketing and data science meet. Data science and marketing are two of the key driving forces that help companies create value and stay on top in today's fast-paced economy. This course is packed with knowledge and includes sections on customer and purchase analytics, as well as a deep-learning model, all implemented in Python.

This course is designed to show you how to work with one of Python's fundamental packages - NumPy. You will learn what a "package" is and see how to install, upgrade and import it. By the time you finish the course, you'll be comfortable with NumPy' ndarray class, how to slice and reduce the dimensions of its instances, as well as how to quickly refer to the documentation. Furthermore, you'll be ready to take advantage of NumPy's various built-in functions and methods, which we'll use to generate random and non-random data, import and export data to and from Python, find statistical values for a dataset, and clean and preprocess ndarrays. Looking for a NumPy course? Try the Data Preprocessing with NumPy Course for free. Learn the applications of the ndarray and upgrade your Python skills.

Python Prescription - PyRx - Virtual Screening Tool: PyRx is a Virtual Screening software for Computational Drug Discovery. PyRx is a Virtual Screening software for Computational Drug Discovery that can be used to screen libraries of compounds against potential drug targets. PyRx enables Medicinal Chemists to run Virtual Screening from any platform and helps users in every step of this process - from data preparation to job submission and analysis of the results. While it is true that there is no magic button in the drug discovery process, PyRx includes docking wizard with an easy-to-use user interface which makes it a valuable tool for Computer-Aided Drug Design. PyRx also includes chemical spreadsheet-like functionality and powerful visualization engine that are essential for structure-based drug design. PyRx - Virtual Screening Computer-Aided Drug Design Software
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Python Prescription - PyRx - Virtual Screening Tool: PyRx is a Virtual Screening software for Computational Drug Discovery. PyRx is a Virtual Screening software for Computational Drug Discovery that can be used to screen libraries of compounds against potential drug targets. PyRx enables Medicinal Chemists to run Virtual Screening from any platform and helps users in every step of this process - from data preparation to job submission and analysis of the results. While it is true that there is no magic button in the drug discovery process, PyRx includes docking wizard with an easy-to-use user interface which makes it a valuable tool for Computer-Aided Drug Design. PyRx also includes chemical spreadsheet-like functionality and powerful visualization engine that are essential for structure-based drug design.

Python Prescription - PyRx - Virtual Screening Tool: PyRx is a Virtual Screening software for Computational Drug Discovery. PyRx is a Virtual Screening software for Computational Drug Discovery that can be used to screen libraries of compounds against potential drug targets. PyRx enables Medicinal Chemists to run Virtual Screening from any platform and helps users in every step of this process - from data preparation to job submission and analysis of the results. While it is true that there is no magic button in the drug discovery process, PyRx includes docking wizard with an easy-to-use user interface which makes it a valuable tool for Computer-Aided Drug Design. PyRx also includes chemical spreadsheet-like functionality and powerful visualization engine that are essential for structure-based drug design.

This course offers a deep dive into an advanced neural network construction - Convolutional Neural Networks. First, we explain the concept of image kernels, and how it relates to CNNs. Then, you will get familiar with the CNN itself, its building blocks, and what makes this kind of network necessary for Computer Vision. You'll apply the theoretical bit to the MNIST example using TensorFlow, and understand how to track and visualize useful metrics using TensorBoard in a dedicated practical section. Later in the course, you'll be introduced to a handful of techniques to improve the performance of neural networks, and a huge real-world practical project for classifying fashion items pictures. Finally, we will cap it all off with an intriguing look through the history of the most influential CNN architectures. Looking for a convolutional neural networks course? Try the Convolutional Neural Networks in Python Course for free. Start now!

Data Science mainly relies on working with two types of data - cross-sectional and time series. This course will help you master the latter by introducing you to ARMA, Seasonal, Integrated, MAX, and Volatility models as well as show you how to forecast them into the future. Looking for a course on Time Series Analysis in Python? Learn more about ARMA, Seasonal, Integrated, MAX, and Volatility models and their forecasting. Try now!

pandas are one of today's most successful data analysis libraries out there. A favorite to many, its versatile functionalities can be leveraged for manipulation of many types of data - numeric, text, Boolean, and more. That's one of the features that make pandas the go-to choice for analysts, especially during the data cleaning and preprocessing stages. Technically, pandas have been built on NumPy because the former need the computational power and abilities of the latter. But what makes pandas truly great is their ability to operate with the data in an easy-to-use way, allowing you to focus almost entirely on your analytic task. And in this course, you will learn how to work with this powerful Python library and its core data structures - the pandas Series and DataFrames. Looking for a pandas course? Try the Data Cleaning and Preprocessing with pandas Course for free. Start now!

Get acquainted with a data science topic of your choice. These explainer videos give you a peek into any topic in less than 2 minutes.