FinTech Bootcamps Milwaukee, WI

In this FinTech Bootcamp, participants learn how to use Python for financial analysis, machine learning and automation, and SQL. The program is taught by seasoned finance and data science professionals. Students will develop the ability to analyze financial statements, build predictive models, and work with databases. By the end of this course, newly-hired financial analysts will be prepared to succeed on the job, and aspiring financial analysts will have bolstered their resumes and technical interview skills. This course offers a free retake so students can refresh the material. It also includes one-on-one mentoring sessions.

Learn Python for financial analysis, machine learning, and algorithmic trading from experienced finance & engineering professionals in this 60-hour immersive.

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.

Learn to problem solve, and effectively communicate, like an analyst. This course teaches you to use industry-standard tools to make ethical, data-driven decisions. Experience hands-on training to master SQL, Excel, Tableau, PowerBI, and Python – tools listed in virtually every data analytics job posting across industries.

Upskill and take your finance skills to the next level with this Python for Finance class. You'll learn to analyze large amounts of financial data using Python, create visualizations, and start using statistics for predictive modeling. 

In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.

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 Python for Finance Immersive course gives students a deep understanding of the use of Python for data extraction, analysis, and visualization. Throughout the 30-hour program, the students will work with NumPy, Pandas, Matplotlib and other scientific libraries as they learn how to pull and process data. Students will graduate with hands-on experience working with Jupyter Notebook, having completed small projects using Python to analyze data. This program is open to beginners, with no requirement for experience in advanced mathematics or coding.

This machine learning course is meant for learners looking to master the concepts needed for machine learning. Students will learn how machine learning can be used for decision-making, the different machine learning techniques available, and how to tackle machine learning projects. The course covers various techniques in machine learning, including regression, classification, k-means, neural networks, and more.

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.