Best FinTech Classes Online

Offered through University of California San Diego Extension, this course prepares advanced programmers for careers in machine learning. Students start with learning about and analyzing data, before moving into machine learning algorithms and deep learning. Students gain hands-on experience developing machine learning platforms and have the option of specializing in advanced deep learning, image processing, or natural language processing with additional study. Career coaching is integrated into the course curriculum, and students produce a machine learning capstone project for their professional portfolio.

After studying this course, complete beginners will have a foundational understanding of SQL. In the first unit, students learn to use SQL for making selections, cleaning data, joining tables, and writing queries and subqueries for analyzing data. In the second unit, students learn tools for managing both relational and non-relational databases, including PostgreSQL and MongoDB. Each unit offers students the opportunity to complete a hands-on project with their new skills.

Beginners in this course learn the tools and concepts necessary for expert database management. Students work primarily with SQL as they gain experience with data manipulation before moving on to work with tables, clauses, queries, indexes, data warehouses, and schemas as they learn to structure queries. Students also learn to use industry-standard database management tools including Microsoft SQL Server and Visual Studio and Oracle Database. When they complete the course, students graduate with a certification issued by Austin Peay State University continuing education, recognized by the global CPD Certification Service.

For students pursuing a careers as a Microsoft Certified Azure Data Scientist Associate, this course helps prepare for the exam. The course covers subjects on the exam such as data processing and statistical analysis as well as principle component analysis and logistic and linear regression. Students also gain experience with decision trees and hyperparameter tuning as well as cluster analysis and K-means clustering. At the end of the course, students earn a certificate of completion.

Students who have some familiarity with corporate finances and spreadsheets can study this course to learn how add financial modeling into their skill set. The course is activity-based, and students build a three-statement model while the videos demonstrate the practice. Students develop familiarity with FCFF and FCFE as they create a DCF valuation, then learn to build forecasts. By the time they finish the course, students will have created a financial model Alphabet.

Through this course, students gain a thorough understanding of performing financial modeling and valuation with the aid of Microsoft Excel. The class begins with an orientation to Excel before demonstrating useful functions and PivotTables. Students work through charts and case studies, learning about profit and loss, financial modeling, company valuation, and capital acquisition, as well as mergers and acquisitions. Upon finishign the course, students earn a certificate of completion.

In this course, students learn hands-on how to write and use SQL code. The class starts with an survey of the syntax before diving into working with data in databases and tables. Students learn to use commands, functions, and operators as they start analyzing data. By the end of the course, students will have also picked up helpful skills in JavaScript and NodeJS as they conclude with a project: developing a web application using MySQL.

In this course, students interested in learning about machine learning gain hands-on experience. Working with Python, students learn about regression, clustering, Bayesian methods and decision trees, and support vector machines. The course also covers reinforcement learning and collaborative filtering as well as ensemble learning, frequency, experimental design, and A/B testing. By the end of the course, students will be able to tackle the final project, and also understand how to scale up machine learning with Apache Spark.

By taking this course, students can gain proficiency in performing financial modeling tailored to small business and startup scenarios. The class demonstrates financial modeling through multiple case studies, sharing best practices for accurate results. Students learn to model growth, revenue, costs, and expenses for small businesses and startups. At the end of the course, students can earn a certificate of completion.

This substantial ten-part course introduces students to the area of machine learning in data science. Students start by learning essential skills with Python and R then work with regressions, classifications, and clustering. Then, students learn algorithms and start using them to solve problems before discovering Natural Language Processing, deep learning, and gradient boosting. By the end of the course, students will have worked on multiple hands-on exercises for cementing their new knowledge of machine learning.

Designed for students who have skills with Python and probability, this machine learning course focuses exclusively on leveraging Bayesian machine learning for A/B testing. Students develop familiarity with the explore-exploit dilemma and the Epsilon-Greedy algorithm. The course also guides students through the UCB1 algorithm. Practical activities allow students to gain hands-on experience with the Bayesian method before they earn their certificate of completion.

In this course track, students develop a solid foundation in SQL. The course starts with an introduction to databases and SQL syntax before moving through using SQL to modify data and create reports. Students learn to write queries and Common Table Expressions before practicing on an example dataset. For troubleshooting and general studying support, students can turn to the Treehouse learning community of peer learners.