What this course is about The Data & Analytics path from IBM SkillsBuild gives you a practical and job-ready introduction to working with data — from gathering and cleaning data, through analysis and visualization, to delivering insights that drive business decisions. You’ll learn how data powers decision-making across industries and gain hands-on experience with tools and techniques used by real data professionals. Whether you aim to become a data analyst, business intelligence reporter, or data-driven consultant, this course gives you a strong foundation to start from. As you complete the learning path, you’ll earn a verified digital credential from IBM that you can add to your resume, LinkedIn profile, and Credly account, demonstrating your competencies in data and analytics. You’ll learn how to: Understand what data analytics is and why it matters

• Work with real data: cleaning, transforming, analyzing, and visualizing
• Use modern data tools (spreadsheets, Python, SQL, BI platforms)
• Present data insights clearly and professionally
• Build a foundation for data-driven roles across industries

What you will learn By the end of this learning path, you will be able to: Understand data analytics basics

Explain what data analytics is and the role it plays in business and decision-making.

Recognize different data roles (e.g. data analyst, BI analyst, business analyst, data scientist) and what each role does. Collect, clean, and wrangle data

Learn the data analysis workflow: gathering data from sources, cleaning and transforming datasets to make them usable. Understand the importance of data quality as a basis for reliable analysis and insights.

• Analyze and summarize data

Apply statistical and analytical techniques to uncover trends, patterns, and insights.

Use tools such as spreadsheets (Excel), SQL databases, or programming languages (like Python with Pandas, NumPy) to manipulate and query data. Visualize data and communicate insights

Create charts, dashboards, and visual reports using BI tools or programming-based libraries to turn raw data into understandable insights.

Present findings in a clear, professional manner so they can inform decisions or business actions. Apply skills in real-world scenarios and build a portfolio

Work on practical projects and case studies that simulate real data workflows — from raw data to insight delivery.

Build a set of demonstrable analytics skills that employers recognize and value.

• Prepare for data-related careers

Understand what employers look for in entry-level data and analytics roles (skills, tools, mindset) and how to position yourself.

Earn a shareable credential that enhances your resume or LinkedIn profile as proof of your readiness for data jobs.