FinTech Bootcamps Chicago, IL

This 24-week program gives students a comprehensive background in FinTech, covering topics such as Python programming, blockchain, advanced trading algorithms, and cryptocurrency. Students will create a professional portfolio to demonstrate their expertise to professional employers. Dedicated career services will support graduates as they look for their first job.

This 1-week data analytics 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 critical data analysis libraries like Numpy, Pandas, and Matplotlib to perform data analysis and create data visualizations. This 35 hour intensive is meant to quickly get beginners in Python up to speed on performing data analysis and visualization in Python.

In this 3-day bootcamp, beginners will be transformed into confident SQL users who can write queries, manipulate tables, and store advanced code. Participants will start by learning about relational databases and SQL fundamentals and will conclude the program having mastered complex retrieval tasks and storing complex code. Topics include composing queries, creating your SQL databases, automating workflow with stored procedures, and step-by-step exercises that will provide an efficient and thorough approach to mastering SQL. Tuition includes hands-on training, a free retake, and a course manual. The course has flexible scheduling options and is available online and in NYC.

In this 18-hour SQL Bootcamp open to beginners, participants will discover the essentials of databases and how to write SQL code to retrieve and analyze data. Through hands-on exercises, participants learn everything from data types to basic queries and advanced topics, including aggregating and joining. Topics include SQL GUI basics, fundamental to advanced querying, table creation, joins, views, functions, and external data connections. The course is taught using PostgreSQL and applies to other relational databases, including SQL Server and MySQL. Participants can retake the course for free within one year.

This 3-day SQL Bootcamp consists of three courses (Levels 1-3) and helps students with little to no prior SQL experience go from novice to pro in a couple of days. The first course, SQL Level 1, covers the basics, including an introduction to SQL and relational databases, the graphical user interface (GUI), and some of the coding basics. The second course, SQL Level 2, introduces students to SQL queries and subqueries, using JOINS, math and logic functions, as well as variables and user functions. The third and final course, SQL Level 3, walks students through importing and exporting data, building control structures, temporary tables, and stored procedures. Each course concludes with student labs to help cement the skills students learn in each course.

Python + Data Science Bootcamp teaches full-stack web development and data science using Python in 10 weeks. If you're accepted to this program, there is three weeks of prework you'll have to complete before starting the program. The program covers HTML/CSS, JavaScript, APIs, frameworks, and more to build front-end applications. After you've learned front-end development, you'll transition to Python and learn its data science packages. In the end, you'll combine your knowledge and create a capstone project to showcase to potential employers.

This 18-hour course teaches the foundational concepts of SQL. Beginners can learn the basic functions of SQL, including the use of tables, queries, and timestamp functions. This program uses Postgres, but skills learned in this course will also translate for use of other systems such as SQL Server. Students in this program get hands-on training in small classes and will graduate with the skills needed to begin a career in SQL.

The Deluxe Data Analytics Track covers course material from both the introductory and advanced level Data Analytics courses. More specifically, this includes learning about Python, Excel, Power BI, and SQL for data analysis, visualization, and optimization.