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Live Session Schedule 🕘

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Morning Live Class

10:00 AM - 11:30 AM CT

Core | Data Analytics

Instructor: Ken Wood

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Evening Live Class

7:30 PM - 9:00 PM CT

Core | Data Analytics

Instructor: Othmane Benyoucef

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Student Success Managers’ Schedule

Course Overview 📚

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Here’s What You’ll Learn, Build, and Achieve

Throughout the Coding Temple Data Analytics program, you will gain a diverse set of in-demand skills that will make you stand out in the job market. You’ll master tools like Excel, SQL, Python, Tableau, and R, and learn how to apply them in real-world projects. By the end of the course, you will have built a competitive portfolio, showcasing your ability to:

• Analyze and visualize data to extract meaningful insights
• Build interactive dashboards to tell compelling data stories
• Apply machine learning techniques to solve predictive modeling problems
• Manage and query large datasets using advanced SQL techniques
• Data-focused Roles Across Various Industries </aside>

Module 1: Foundations of Data Analytics

This module builds a strong base in the core principles of data analysis, including statistical theory, data ethics, and essential analytical tools. Students explore the full analytics process—from managing raw data to drawing insights—while also being introduced to modern tools that streamline and enhance analysis through automation and intelligent recommendations.

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Module 2: Microsoft Excel

This module immerses students in Excel, starting with foundational tasks and advancing toward real-world data analysis applications. From data cleaning and formatting to statistical modeling and visual storytelling, students gain hands-on experience using Excel’s core capabilities—alongside emerging tools that bring intelligent automation into the workflow.

Key elements of the module

Module 3: SQL and Relational Databases

This module introduces students to the structure and function of relational databases, focusing on how SQL is used to store, query, and manipulate data. Students learn how to build databases from the ground up, write complex queries, and work with large datasets in modern environments—while also exploring the evolving role of intelligent systems in query generation and validation.

Key elements of the module

Module 4: R Programming

This module introduces students to R, a powerful language for statistical analysis and data visualization. Through hands-on coding and real-world projects, students learn to manipulate data, conduct complex analyses, and create insightful visuals—while also gaining exposure to modern tools that support code generation, optimization, and debugging.