Python Classes Salt Lake City, UT

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.

Embark on a data-driven career with Utah State University's Data Analytics Bootcamp, powered by Fullstack Academy. This 10-26 week online program, suitable for beginners and those aiming to enhance their skills, delves into critical tools such as Excel, SQL, and Python and guides you towards industry certifications, culminating in a project that prepares you for roles like Data Analyst and Insights Analyst.

In the Python for Data Science Masterclass, students learn both foundational and advanced Python programming skills, including data types, control flow, and object-oriented programming. The curriculum covers data science libraries like NumPy and Pandas for data manipulation and Matplotlib and Seaborn for data visualization. The course also covers advanced techniques such as web scraping, database querying, and using APIs.

Create dashboards and other interactive visualizations with Python and its libraries in this hands-on course. Participants will also learn how to deploy projects online using Heroku server and GitHub.

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 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.