Data Science Classes Nashville, TN

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.

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.

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.

Earn a Python certification with hands-on training in data analysis, machine learning, and real-world projects to prepare you for the PCAP exam and beyond.

Build a strong foundation in Python, SQL, and machine learning through self-paced, expert-supported training designed for aspiring data scientists. You’ll gain real-world experience through hands-on projects and capstone work that prepares you for entry-level roles in data science and automation.

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.

Ready yourself for a data analytics career with this fifteen-week bootcamp. Through hands-on learning in commonly used tools, such as Power BI, Tableau, Excel, SQL, and Python, students use statistical reasoning to solve everyday problems in the business world. This bootcamp also covers analytics workflow, exploratory data analysis, and reporting techniques. Participants learn more than theories. They also use real information from area businesses to perfect their data analytics skills.

In this course, students discover the essentials of machine learning. By learning to work in Python, students gain familiarity with object-oriented programming and neural networks.