Python Classes Virginia, US

In this comprehensive data science program, individuals will learn a variety of critical skills to become a data scientist. Students will learn to code with Python, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Topics include data analysis with Python's Numpy and Pandas packages, data visualization, predictive analytics, machine learning, SQL querying, Python automation, and web scraping. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake for students to refresh the material.

In this course, students expand their Python programming skills into machine learning and algorithms that can independently learn patterns and make decisions. The course begins with linear and logistic regressions, the most time-tested and reliable tools for approaching a machine learning problem. Students then progress to algorithms with a different theoretical basis, such as k-nearest neighbors, decision trees, and random forest. This will bring important statistical concepts to the forefront, such as bias, variance, and overfitting. Participants also learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms.

Learn the essential skills and tools to become a Python Developer. This beginner-friendly course teaches students Python for software development with Django and Django REST in addition to other developer tools such as Git and SQL. After completing this certificate, students will be able to apply for the following roles: Python Developer, Back End Developer, Software Engineer, and many more.

Step into the data-driven world with Virginia Tech's Data Analytics Bootcamp, a Fullstack Academy-powered program. This online course, spanning 10 to 26 weeks, provides in-depth training in tools like Excel, SQL, and Python and equips students with hands-on experience for roles such as Data Analyst and Insights Analyst.

Transform your career with Virginia Tech's AI & Machine Learning Bootcamp, an innovative program powered by Fullstack Academy. Over 26 weeks in this part-time, online course, students explore the practical and theoretical aspects of AI and machine learning, using real-world tools to prepare for roles in the rapidly growing data field.

The Fullstack Academy Artificial Intelligence & Machine Learning bootcamp provides current and prospective data professionals with the in-demand skills to specialize in this lucrative, dynamic, and rapidly-growing field. Over 26 weeks part-time, students will learn practical and theoretical machine learning concepts using real-world tools—graduating with the working knowledge and experience needed to qualify for a range of data roles, including those concentrated in AI. Students will also receive professional career coaching support for up to a year following graduation to help build and maintain an ideal, specialized career path in the industry.

This course on data wrangling with Python offers a 3-day comprehensive introduction. The purpose of this course is to give an immersive foundation that equips students with the most critical data analysis tools. Students will learn how to work with NumPy, Pandas, and MatPlotLib to calculate descriptive statistics, work with alternative data sources, and scrape web pages. The course culminates with a real-life data wrangling project.

This 2-day course provides a deep-dive into using Python for data analysis. Students will get comfortable with the basics of Python programming and start working with Numpy Arrays, pandas, and MATPLOTLIB to perform data analysis and create data visualizations. This intensive course is meant to quickly get beginners in Python up to speed on performing data analysis and visualization in Python.

This 5-day introductory Python programming course is designed for students with no prior programming experience and are looking to get comfortable with basic skills needed for Python programming. This skills-centric course will cover foundational Python concepts, including data types, control statements, using functions and modules, handling exceptions and debugging programs, working with lists, and how to work with a variety of data types. By the end of the course, students will be familiar with writing programs to create real-world Python applications.

This 3-day advanced Python programming course is designed for students already familiar with Python programming who are looking to understand more advanced procedures. This course will cover a range of advanced Python concepts, including classes and objects, methods, inheritance, the importance of the Standard Library, working with the OS, advanced comprehensions, as well as testing and debugging programs. Students will also learn how to package an application for distribution.

In this 2-day introductory Python course, participants will learn the fundamentals of Python programming. This hands-on course will give students with no prior Python experience the foundational programming skills needed to continue learning Python’s applications in data science or web development. Topics include Python environment setup, programming concepts, data structures, exceptions, Python syntax, and more.

In this Python automation course, students will learn to automate tasks using Python for various applications. This course is meant for those with prior Python experience looking to learn automation techniques like scheduling programs, updating spreadsheets, and web scraping. Topics include HTML and CSS basics, web scraping techniques, working with spreadsheets using Python, and scheduling scripts. This course offers flexible scheduling options plus a free retake for students to refresh the material.

This introductory Python Programming course covers data types, writing functions, mathematical and datetime modules, and string formatting. Once the basics are covered, it dives into flow control such as loops, list comprehensions, enumerations, and is-is not operators. Finally, it takes a look at using virtual environments, command lines, and file processing to execute Python files.

Advanced Python Programming covers lambda functions, mapping & filtering, sorting, and advanced topics such as mutable and immutable built-in objects. This course also introduces topics such as inheritance, attributes, methods, and properties. You'll apply what you've learnt by using an API to get data from a website, saving it into a CSV, and cleaning it up using Python.

This 2-day course on Python with data science is intended for software developers, IT architects, and data scientists. This course will build on their knowledge of statistics and programming, teaching them the theoretical and technical aspects of the use for Python. Students will learn about the history and purpose of data science, life-cycle phases of data analytics, methods for repairing and normalizing data, and how to aggregate and group data. Students will also complete 10 lab exercises.

Apply Python skills to your data science career in this five-day intermediate course. Software engineers, data scientists, and data engineers all benefit from this course. Specific course topics include a Python review, iPython fundamentals, numpy number sets, scipy subpackages, panda dataframes, matplotlib plots, the Python image library, seaborn data visualization, SciKit classification, TensorFlow overview, PySpark, and Spark SQL, MLib, and streaming.

Explore some Python programming basics in this three-day, beginner-level course. Participants learn how to write professional-grade programs that optimize workflow and empower decision makers. Specific course topics include a Python overview, linguistic basics, sophisticated operations and types, control structures, information statements, functions, classes, and modules.

Learn Python basics like functions, unit testing, and features in this four-day introductory course. Participants learn how to use this simple yet powerful programming language to solve everyday problems. Specific course topics include a Python introduction, syntax basics, types, collections, functions, classes, error messages, I/O files, Pyramid web applications, Python iterations, NoSQL, ORM, and Mongo databases, redistributables, and debugging procedures.

This four-day, intermediate level Python class focuses on enterprise-level problems and solutions. Participants acquire these skills through a 50-50 combination of hands-on learning and live instruction. Specific course topics include a Python refresher, essential OS skills, binary data, dates and times, functions, packages, models, metaprogramming, development, testing, database architecture, network programming, multiprogramming, data serialization, advanced data handling, and information scripting.