FinTech Classes California

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 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.

The AI & Machine Learning Bootcamp at the University of San Diego, powered by Fullstack Academy, offers a dynamic 26-week part-time curriculum, welcoming students from various professional backgrounds into the world of artificial intelligence and machine learning. This program blends theoretical knowledge with practical application, using lectures, labs, and projects to equip students with the skills needed for existing roles or new careers in the data field.

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.

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 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.

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.

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

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 introduction to Blockchain covers the Ethereum blockchain, smart contract development, DAPP development, and how to create private blockchains. You'll also set up the development environment and all pre-requirements from a clean Microsoft Windows image, making the course easy to follow. This 4-week program prepares you to create your own blockchain contracts and distributed applications with a functional development environment that makes you productive for years to come.

Embark on a career-transforming journey with the University of San Diego's AI & Machine Learning Bootcamp, a part-time, 26-week course created in association with Fullstack Academy. This program, ideal for individuals from diverse professional fields, offers an immersive online education in AI and machine learning principles. Engaging in lectures, labs, and practical projects, you'll develop the essential skills to implement AI solutions in the fast-expanding world of data technology.

Analyze data and use it to solve real-world problems with this 10-week Python course. This platform enables users to leverage complex data into an easy-to-understand format. Primarily using Pandas, a key data analysis platform, students learn to prepare, cleanse, format, convert, and present data. Use of statistical models and some basic data visualization techniques greatly assists this process. Course prerequisites include a beginner Python programming course or equivalent experience.

This financial modeling bootcamp is geared towards students or analysts in business or finance looking to gain skills in financial modeling. Participants will learn hands-on by building financial models in the course. This course covers DCF modeling, finding key financial information online, tying together financial statements, and creating LBO and M&A models.

This financial modeling course teaches the commonly-used valuation and modeling techniques. Students will learn fundamental Excel and finance skills needed for financial modeling, build a DCF model, create an M & A model, and make an LBO model.

In this advanced modeling course, students will focus on M&A and LBO analyses. Students will learn key accounting and finance concepts for each type of analysis as they build towards a full project analysis. This course features a mix of instructor teaching as well as project work building an M&A model as well as an LBO model.

This Python and machine learning course is a 2-day bootcamp designed for individuals with some familiarity with Python programming looking to advance their skill set. In this hands-on bootcamp, students will learn how to use some Python data science libraries and various machine learning techniques. Day one of the bootcamp focuses on introducing students to two data science libraries (NumPy and Pandas), best practices for preparing data, an intro to machine learning, and regression analysis. Day two starts off with cross validation and regularization of data, concludes with classification, and brings everything learned in days one and two together.

This SQL bootcamp is a beginner-friendly workshop designed for individuals with no prior knowledge of SQL who are eager to learn. In this hands-on workshop, students will learn the basics of SQL syntax and how databases are organized. Students in this course will also learn how to query data, aggregate data with statistical functions (SUM, AVG, COUNT, etc.), group data, and use conditional operators (=, <, >, etc.) to sort and filter data, and much more. Students will also learn when and how to use UNIONs and JOINs to merge data to spot trends and other insights.

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.

In this beginner Excel class, students will learn the fundamental skills of Excel with hands-on work. This course starts with the basics of Excel setup and best practices. After that, students will learn to work with text, analyze data, perform scenario analysis, and start working with macros.