Python Programming

Obtain the foundational skills needed to begin your goal of becoming a programmer. This course introduces first-time programmers to basic programming techniques and principles using the popular Python Programming language. Python's simple syntax is similar to the English language making it easy to comprehend and allows programmers to write code with fewer lines. This course serves as a good starting point for students looking to further their training in the Python programming language. Course Highlights: Rules and syntax applicable to a modern programming language Understanding and...

Python Programming Fundamentals Python is a versatile and powerful programming language with a wide variety of libraries and third-party packages that can be applied to deep learning, fuzzy text processing, bioinformatics, web development, web scraping, and more. Building off of Introduction to Programming (Python), this course will cover many unique features that make Python such a popular language, and will go beyond just "the basics." Upon completion of the course, students will gain experience in the full development life cycle using the Python programming language. Course Highlights:...

Intermediate Python This course utilizes the power and flexibility of the Python language to apply practical programming strategies such as the functional paradigm, modularity, parallelism, concurrency, metaprogramming, reactive programming, microservices, and design patterns. Students will learn when and how to apply their knowledge and understanding to achieve optimal solutions to a variety of software problems. Prior knowledge of the Python language is required for this course. To prepare for this course, students should take Intro to Programming Python and Python Programming...

Data Analytics Using Python In this course, you will learn the rich set of tools, libraries, and packages that comprise the highly popular and practical Python data analysis ecosystem. This course is primarily taught via screen sharing programming videos. Topics taught range from basic Python syntax all the way to more advanced topics like supervised and unsupervised machine learning techniques. Key topics: Installing Python/Jupyter/IPython on Windows and Mac Python Basics (variables, strings, simple math, conditional logic, for loops, lists, tuples, dictionaries, etc.) Using the Pandas...

Python for Informatics Informatics is the study of structure, algorithms, behavior, and interactions of information systems. Its applications are powerful and broad, and include such fields as life sciences, data mining, business analytics, and social computing. This hands-on course introduces the Python programming language, and is targeted toward students without prior programming experience who are interested in how informatics can be employed to provide solutions to complex, data intensive problems in a variety of scientific and business domains. After learning the core syntax and...

Software unit tests help the developer to verify that the logic of individual pieces of the program is correct. It is vital to the success of refactoring, the act of improving software design without changing the behavior of the system. In this course, students will learn how to use both Python's built-in unit test module and the Pytest module as a unit testing framework for the Python programming language. This includes the Pytest features of Fixtures and the rich plug-in ecosystem for Pytest. The key unit testing concepts of Behavior-Driven Development (BDD), Test-Driven Development...

Design and Build Web Applications using Python Web Frameworks Python is rapidly becoming a favorite programming language for developing responsive websites, due in large part to the excellent availability of web frameworks. Web frameworks are Python packages that provide a suite of tools built-in that allow rapid development and deployment of websites. In this course, students will gain experience with the popular Django web framework to design, develop and implement a web application. The curriculum covers front-end-coding and back-end libraries for frameworks, optimization, and security...

Elevate Your Python Programming Mastery with Data Structures and Algorithms Our algorithm and data structures course will teach you how to write code that scales with large data sets and identify hidden performance bottlenecks. While the concepts covered in this course are addressed in Python, they can be applied to all programming languages and software development domains. By the end of this course, you’ll have a strong understanding of fundamental algorithms and data structures and be equipped to answer commonly asked interview questions. Course Highlights: Algorithmic Foundations Search...

Data Science with R Data management and manipulation is an essential task for data scientists who deal with data on a day-to-day basis. In recent years, many R packages were developed to tackle a wide variety of data science challenges. The focus of this course is the tidyverse suite of packages, which contain a large variety of tools to efficiently manage complex and big data. The materials in this course are essential for developing robust and efficient R programs in the data science field. At the end of this course, students will be able to work independently to solve common data...

GIS I: Introduction to GIS The ability to analyze and manipulate spatial data is critical across many industries, including urban planning, healthcare, agriculture, mining, trade, environmental science, and military intelligence. The demand for skilled GIS analysts is projected to grow rapidly in the coming years, as this specialized area of data analysis is leveraged in an expanding number of fields. In this introductory course, you will learn the fundamentals of geographic information systems (GIS). Upon completion of the course, you will be able to display, analyze, and store spatial...

Introduction to R Programming Statistical computing is employed within a diverse range of industries. In recent years, an open source project, R, has emerged as the preeminent statistical computing platform. With its unsurpassed library of freely available packages, R is capable of addressing almost every statistical inference problem. In this course, you will learn the most commonly-used (roughly 100) functions and operators from the R Base Package, which serves as the fundamental tools for accessing data from multiple sources, manipulating different types of R objects, performing...