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Skills Covered: Data Analytics, Data Structures, Data Gathering, Data Wrangling, Data Mining, Data Analysis, Data Visualization, Data Analysis with Excel, Building Dashboards, Cognos Analytics, Data Science using Python, Python Programming, Numpy Arrays, Python Data Structures, SQL for Data Science, Visualization Tools, Visualizing Geospatial Data

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This eight-course Professional Certificate from IBM prepares you with job-ready skills for an entry level data analyst role. Position yourself competitively and power your data analyst career for a job in a thriving market or leverage foundational data skills to explore problems in an increasingly data-driven professional world. The U.S. Bureau of Labor Statistics projects a growth rate of 20% in the data analytics industry until 2028.

You will learn the core principles of data analysis, participate in hands-on skills-based practice, and gain the knowledge to help companies make smarter business decisions. You will work with a variety of data sources, project scenarios, and data analysis tools, including Excel, SQL, Python, Jupyter Notebooks, and Cognos Analytics. These online learning tools will offer you practical experience with data manipulation and the application of analytical and data visualization techniques.

This Professional Certificate does not require any prior programming or statistical skills, and is suitable for learners with or without college degrees. A willingness to learn, basic computer literacy, comfort working with numbers, high school math, and a desire to enrich your profile with valuable skills is all you need to get started in this course.

With the IBM Data Analyst Professional Certificate you will develop the confidence and portfolio to begin a career as an associate or junior data analyst by learning the essential skills that help professionals in a wide range of job functions and industries explore business problems.



  • Create charts and plots in Excel, and work with IBM Cognos Analytics to build dashboards.
  • Describe the data ecosystem and Compose queries to access data in cloud databases using SQL and Python from Jupyter notebooks.
  • Develop a working knowledge of Python language to analyze data using Python libraries like Pandas and Numpy, and invoke APIs and Web Services.
  • Perform data analysis tasks like data mining and data wrangling using Excel spreadsheets and Jupyter Notebooks.
  • Visualize data using Python libraires like Matplotlib, Seaborn, and Folium.



  • Data Analytics and Science professionals in the US have an average starting salary of over $80,000.
  • Data Analysts are in demand, with 20% growth expected through 2028 (U.S. Bureau of Lab Statistics)
  • Over 2.5 Million jobs in data science and related professions (Burning glass).
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Data Analyst by IBM
Data Analyst by IBM


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