Data Science Bootcamps Nashville, TN

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.

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.

Create robust predictive models with statistics and Python programming. Build confidence and credibility to tackle complex machine learning problems on the job. This course is offered in person and live online, in a remote classroom setting.

Harness Excel, SQL, and Tableau to drive powerful analysis and insights. Build confidence and credibility to apply this versatile skill set to countless jobs. This course is offered in person and live online, in a remote classroom setting.

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.

Data Science Flex is a 6-month part-time program that will prepare you to to be a data scientist. This program comes with a tuition back guarantee if you can't land a job within 6 months after your graduation. To be accepted into this program, you will have to complete 3 weeks of prepwork and pass an assessment test before you start. Once you're accepted, you'll learn how to clean data using Python, query data using SQL, learn how to train and evaluate supervised and unsupervised machine learning models, and choose a track to specialize. You can deepdive in natural language processing, big data and spark, and deep learning with TensorFlow and Keras.

Launch your data science career with this nine-month bootcamp. Motivated working professionals with a background in software engineering, quantitative research, and/or statistical reasoning benefit most from this class. Data science essentially combines all three of these disciplines. Through hands-on learning, students apply mathematical, analytical, and statistical skills to real-world business problems, using tools such as Python, AWS, Spark, and Hadoop. Overall concepts include curating and managing data, exploratory data analysis, supervised and unsupervised machine learning, data visualization, and natural language processing.

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 six-month part-time data analytics boot camp effectively prepares working professionals for a new career in this emerging field. Through hands-on learning in widely-used tools, such as SQL, Power BI, Tableau, Python, and Excel, students apply statistical reasoning to everyday business problems. This process uses actual data from local companies in a variety of business lines. Participants also examine concepts like analytics workflow and exploratory data analysis. Finally, students learn how to use storytelling, dashboards, and report-building to effectively present their findings.