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Prepare for a career in data analytics. Gain the in-demand skills and hands-on experience to get job-ready in less than 3 months. No prior experience required.
Instructors: IBM Skills Network Team
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Beginner level
No prior experience or degrees required.
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Recommended experience
Beginner level
No prior experience or degrees required.
Master the most up-to-date practical skills and knowledge data analysts use in their daily roles
Learn how to perform data analysis, including data preparation, statistical analysis, and predictive modeling using R, R Studio, and Jupyter
Utilize Excel spreadsheets to perform a variety of data analysis tasks like data wrangling, using pivot tables, data mining, & creating charts
Communicate your data findings using various data visualization techniques including, charts, plots & interactive dashboards with Cognos and R Shiny
Add to your LinkedIn profile
Prepare for the in-demand field of data analytics. In this program, you’ll learn high valued skills like Excel, Cognos Analytics, and R programming language to get job-ready in less than 3 months.
Data analytics is a strategy-based science where data is analyzed to find trends, answer questions, shape business processes, and aid decision-making. This Professional Certificate focuses on data analysis using Microsoft Excel and R programming language. If you’re interested in using Python, please explore the IBM Data Analyst PC.
This program will teach you the foundational data skills employers are seeking for entry level data analytics roles and will provide a portfolio of projects and a Professional Certificate from IBM to showcase your expertise to potential employers.
You’ll learn the latest skills and tools used by professional data analysts and upon successful completion of this program, you will be able to work with Excel spreadsheets, Jupyter Notebooks, and R Studio to analyze data and create visualizations. You will also use the R programming language to complete the entire data analysis process, including data preparation, statistical analysis, data visualization, predictive modeling and creating interactive dashboards. Lastly, you’ll learn how to communicate your data findings and prepare a summary report.
This program is ACE® and FIBAA recommended—when you complete, you can earn up to 15 college credits and 4 ECTS credits.
Applied Learning Project
You will complete hands-on labs to build your portfolio and gain practical experience with Excel, Cognos Analytics, SQL, and the R programing language and related libraries for data science, including Tidyverse, Tidymodels, R Shiny, ggplot2, Leaflet, and rvest.
Projects include:
Analyzing fleet vehicle inventory data using pivot tables.
Using key performance indicator (KPI) data from car sales to create an interactive dashboard.
Identifying patterns in countries’ COVID-19 testing data rates using R.
Using SQL with the RODBC R package to analyze foreign grain markets.
Creating linear and polynomial regression models and comparing them with weather station data to predict precipitation.
Using the R Shiny package to create a dashboard that examines trends in census data.
Using hypothesis testing and predictive modeling skills to build an interactive dashboard with the R Shiny package and a dynamic Leaflet map widget to investigate how weather affects bike-sharing demand.
Explain what Data Analytics is and the key steps in the Data Analytics process
Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst
Describe the different types of data structures, file formats, and sources of data
Describe the data analysis process involving collecting, wrangling, mining, and visualizing data
Display working knowledge of Excel for Data Analysis.
Perform basic spreadsheet tasks including navigation, data entry, and using formulas.
Employ data quality techniques to import and clean data in Excel.
Analyze data in spreadsheets by using filter, sort, look-up functions, as well as pivot tables.
Create basic visualizations such as line graphs, bar graphs, and pie charts using Excel spreadsheets.
Explain the important role charts play in telling a data-driven story.
Construct advanced charts and visualizations such as Treemaps, Sparklines, Histogram, Scatter Plots, and Filled Map Charts.
Build and share interactive dashboards using Excel and Cognos Analytics.
Demonstrate readiness for performing foundational data analysis and data visualization tasks and key steps in the Data Analytics process.
Differentiate between the roles different data professionals play in a modern data ecosystem.
Perform basic Excel tasks for Data Analysis including data quality and data preparation skills.
Exhibit abilities in visualizing data using Excel and proficiency in creating dashboards using Excel and Cognos Analytics.
Manipulate primitive data types in the R programming language using RStudio or Jupyter Notebooks.
Control program flow with conditions and loops, write functions, perform character string operations, write regular expressions, handle errors.
Construct and manipulate R data structures, including vectors, factors, lists, and data frames.
Read, write, and save data files and scrape web pages using R.
Create and access a database instance on the cloud
Compose and execute basic SQL statements - SELECT, INSERT, UPDATE, DELETE, CREATE, DROP
Construct SQL statements to filter, sort, group results, use built-in functions, compose nested queries, access multiple tables
Analyze data from Jupyter using R and SQL by combining SQL and R skills to query real-world datasets
Prepare data for analysis by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.
Compare and contrast predictive models using simple linear, multiple linear, and polynomial regression methods.
Examine data using descriptive statistics, data grouping, analysis of variance (ANOVA), and correlation statistics.
Evaluate a model for overfitting and underfitting conditions and tune its performance using regularization and grid search.
Create bar charts, histograms, pie charts, scatter plots, line graphs, box plots, and maps using R and related packages.
Design customized charts and plots using annotations, axis titles, text labels, themes, and faceting.
Create maps using the Leaflet package for R.
Create interactive dashboards using the Shiny package for R.
Write a web scraping program to extract data from an HTML file using HTTP requests and convert the data to a data frame.
Prepare data for modelling by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.
Interpret datawithexploratory data analysis techniques by calculating descriptive statistics, graphing data, and generating correlation statistics.
Build a Shiny app containing a Leaflet map and an interactive dashboard then create a presentation on the project to share with your peers.
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
When you complete this Professional Certificate, you may be able to have your learning recognized for credit if you are admitted and enroll in one of the following online degree programs.¹
When you complete this Professional Certificate, you may be able to have your learning recognized for credit if you are admitted and enroll in one of the following online degree programs.¹
Illinois Tech
Degree
¹Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information.
This Professional Certificate has ACE® recommendation. It is eligible for college credit at participating U.S. colleges and universities. Note: The decision to accept specific credit recommendations is up to each institution.
At IBM, we know how rapidly tech evolves and recognize the crucial need for businesses and professionals to build job-ready, hands-on skills quickly. As a market-leading tech innovator, we’re committed to helping you thrive in this dynamic landscape. Through IBM Skills Network, our expertly designed training programs in AI, software development, cybersecurity, data science, business management, and more, provide the essential skills you need to secure your first job, advance your career, or drive business success. Whether you’re upskilling yourself or your team, our courses, Specializations, and Professional Certificates build the technical expertise that ensures you, and your organization, excel in a competitive world.
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This Professional Certificate is self-paced. Learners spending 10-12 hours a week can complete within 6 months. For others it can vary between 3 to 9 months.
No prior experience, degrees, statistical or programming knowledge is necessary. Just the passion to self-learn online, comfort & interest in working with numbers and data, and basic computer literacy.
Yes, it is highly recommended the courses be taken in the order they are presented in the certificate.
This Professional Certificate is intended to prepare you with skills and confidence to take on an entry level role in Data Analytics or Data Science. After completing this certificate program you will be able to: Describe the data ecosystem, tasks a Data Analyst performs, as well as skills and tools required to become a successful Data Analys
Explain basic functionality of spreadsheets, and utilize Excel to perform a variety of data analysis tasks like data wrangling, using pivot tables, and data mining
Create various types of visualizations including charts, and dashboards using Excel and Cognos Analytics.
Perform basic R programming tasks such as using common data structures, data manipulation, using APIs, webscraping, and working with R Studio and Jupyter.
Create relational databases and query the data using SQL and R from JupyterLab
Complete the data analysis process, including data preparation, statistical analysis, and predictive modeling.
Communicate data findings using data visualization charts, plots, and dashboards using libraries such as ggplot, leaflet and R Shiny.
Both this and the IBM Data Analyst Professional Certificate are intnded to prepare you with job-ready skills for an entry level Data Analytics role. The initial three foundational courses, that do not involve any programming, are common between the two programs. The next set of courses in this PC are based on the R Programming language, whereas in the other program they are based on the Python language. Other than that they teach similar concepts and skills. So if you want Data Analysis skills using R, you should enroll in this program whereas is you want Python skills, you can enroll in the ther one. Or you can do both, by first completing one and then the other.
Yes. The IBM Data Analytics with Excel and R Professional Certificate secured a credit recommendation from the American Council on Education’s (ACE) Credit Recommendation, as well as the European Credit Transfer and Accumulation System (ECTS) from the Foundation for International Business Administration Accreditation (FIBAA) – industry standards for translating workplace learning into college credit. This aims to help open up additional pathways to learners who are interested in higher education and prepare them for entry-level jobs.
To share proof of completion with schools, certificate graduates will receive an email prompting them to claim their Credly badge, which contains the ACE®️ credit or ECTS recommendation. Once claimed, you will receive a competency-based transcript that signifies the credit recommendation, which can be shared directly with a school from the Credly platform. Please note that the decision to accept specific credit recommendations is up to each institution and is not guaranteed.
For ACE recommendations, please see Coursera’s ACE Recommendations FAQ. For ECTS recommendations, please see Coursera’s ECTS Recommendations FAQ.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Certificate, you’re automatically subscribed to the full Certificate. Visit your learner dashboard to track your progress.
¹ Median salary and job opening data are sourced from Lightcast™ Job Postings Report. Data for job roles relevant to featured programs (2/1/2024 - 2/1/2025)
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