IBM Data Analyst, Certificate | Part time online | Coursera | United States
4 months
Duration
Free
Free
Unknown
Tuition fee
Anytime
Unknown
Apply date
Anytime
Unknown
Start date

About

Gain the job-ready skills for an entry-level data analyst role through this eight-course IBM Data Analyst couse offered by Coursera in partnership with IBM and position yourself competitively in the thriving job market for data analysts, which will see a 20% growth until 2028 (U.S. Bureau of Labor Statistics).

Visit the Visit programme website for more information

Overview

Power your data analyst career by learning the core principles of data analysis and gaining hands-on skills practice. You’ll work with a variety of data sources, project scenarios, and data analysis tools, including Excel, SQL, Python, Jupyter Notebooks, and Cognos Analytics, gaining practical experience with data manipulation and applying analytical techniques.

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

Upon successful completion of this   IBM Data Analyst couse offered by Coursera , you’ll have analyzed real-world datasets, created interactive dashboards, and presented reports to share your findings, giving you the confidence and the portfolio to begin a career as an associate or junior data analyst. You’ll also build the foundation for other data disciplines such as data science or data engineering.

Applied Learning Project

Throughout the program, you’ll complete hands-on projects and labs and gain a firm grasp on the technical skills required to effectively gather, wrangle, mine, and visualize data, as well as soft skills for working with stakeholders and storytelling with data to engage your audience. 

At the end of the program, you will complete a real-world capstone project specifically designed to showcase your newly learned data analyst skills. 

All these projects can be combined into a portfolio on GitHub or another service to clearly convey your experience and skills to potential employers.

Programme Structure

Courses include:

  • Data Analytics
  • Excel Basics for Data Analysis
  • Data Visualization and Dashboards with Excel and Cognos
  • Python for Data Science and AI
  • Databases and SQL for Data Science
  • Data Analysis with Python
  • Data Visualization with Python
  • IBM Data Analyst Capstone Project

Key information

Duration

  • Part-time
    • 4 months
    • 10 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

What students do after studying

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Beginner Level

  • No degree or prior experience required. All you need is basic computer literacy, high school math, and comfort with numbers. 

Tuition Fee

To always see correct tuition fees
  • International

    Free
    Tuition Fee
    Based on the tuition of 0 USD for the full programme during 4 months.
  • National

    Free
    Tuition Fee
    Based on the tuition of 0 USD for the full programme during 4 months.

You can choose from hundreds of free courses, or get a degree or certificate at a breakthrough price. You can now select Coursera Plus, an annual subscription that provides unlimited access.

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

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