Become a Python Programmer and learn one of employer's most requested skills of 2018! This is the most comprehensive, yet straight-forward, course for the Python programming language on Udemy! Whether you have never programmed before, already know basic syntax, or want to learn about the advanced features of Python, this course is for you! In this course we will teach you Python 3. (Note, we also provide older Python 2 notes in case you need them) With over 100 lectures and more than 20 hours of video this comprehensive course leaves no stone unturned! This course includes quizzes, tests, and homework assignments as well as 3 major projects to create a Python project portfolio!
Here the concept of cubic interpolating splines is introduced. The lecture also discusses the degrees of freedom when constructing such a spline interpolant (the boundary conditions) and outlines how to construct a cubic spline. The downloadable zip file contains the Python example as a Jupyter Notebook (CubicSpline.ipynb) This example shows how to use a SciPy library function to construct a cubic interpolating spline, which was used to create figures for the presentation and is included for reference only. The next section will deal with how actually to construct the splines.
Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create documents that contain live code, equations, and visualizations. This video course is a comprehensive guide to getting started with data science using the popular Jupyter Notebook. If you are familiar with Jupyter Notebook and want to learn how to use its capabilities to perform various data science tasks, this video course is for you! From data exploration to visualization, this course will take you every step of the way in implementing an effective data science pipeline using Jupyter.
About this course: What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.