Data Analytics Classes Raleigh, NC

In this comprehensive data science program, individuals will learn a variety of critical skills to become a data scientist. Students will learn to code with Python, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Topics include data analysis with Python's NumPy and Pandas packages, data visualization, predictive analytics, machine learning, SQL querying, Python automation, and web scraping. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake so students can refresh the material.

In this program, participants will learn the key skills and tools needed to succeed as a data analyst, including Excel, SQL, and Tableau. Attendees will learn how to use Excel to create graphs, summarize data with PivotTables, and analyze data. In SQL, attendees will learn the essentials of relational databases, queries, functions, and more. Finally, participants will learn Tableau to create visualizations to present their data clearly. The program is open to beginners and has flexible scheduling options. Tuition includes hands-on training, a free retake, and training manuals for each course.

In this 8-day intensive Data Analytics bootcamp, students with little to no background in data analytics will learn how to use Microsoft Excel, SQL, and Tableau to summarize, display, and discover key insights hidden in data sets. By the end of this bootcamp, students will be able to use Excel to aggregate and summarize data, summarize and analyze data with PivotTables, create charts and PivotCharts in Excel, use SQL to filter and sort large data sets, perform advanced database queries, create visualizations with Tableau, and much more. Students will also be able to reinforce what they learn through the numerous projects they encounter throughout the course. This course also offers a free retake within six months to allow students to revisit any concepts needing to be refreshed and walk away with a much stronger grasp of the material.

Students build in-demand industry skills and prepare to take certification exams in Tableau and Amazon Web Services. The program consists of Fullstack’s live online classes and workshops so you will feel fully supported along your journey. The up-to-date curriculum ensures course activities are relevant to real-world applications, and interactive technology helps you master the knowledge and skills you’ll acquire throughout the program.

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, Power BI, and Python – tools listed in virtually every data analytics job posting across industries.

Develop a solid design foundation in this two-day beginner-level Tableau training course. Through a combination of hands-on learning, instructor guidance, and class discussions, students import data from multiple sources and use it to create compelling visualizations and engaging stories. Specific topics include the Tableau interface, understanding techniques and best practices, leveraging the Tableau paradigm, workflow management, data analysis, data breakdowns, basic calculations, and guided data presentation.

Take your Tableau skills to the next level in this three-day intermediate course. Using more in-depth Tableau features, such as advanced data visualization techniques, participants solve more advanced problems. Specific topics include a Tableau review, parameters, sets, groups, reference lines, animation features, forecasting, mapping, data sourcing, field calculations, and advanced charting.

Combine basic and intermediate courses in this fast-paced five-day Tableau bootcamp. Once they acquire a solid foundation, students move quickly to more advanced areas through a combination of structured and guided learning. Key concepts include combining visualizations, using interactive dashboards, using data stores, gaining data insights, effective presentation techniques, and sophisticated data charting approaches.