What Is Sales Analytics and How Does It Benefit My Business?
March 4, 2024
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Prepare for a career as a data analyst. Build job-ready skills – and must-have AI skills – for an in-demand career. Earn a credential from IBM. No prior experience required.
Instructors: IBM Skills Network Team
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(21,367 reviews)
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Beginner level
No degree or prior experience required. All you need is basic computer literacy, high school math, and comfort with numbers.
(21,367 reviews)
Recommended experience
Beginner level
No degree or prior experience required. All you need is basic computer literacy, high school math, and comfort with numbers.
Master the most up-to-date practical skills and tools that data analysts use in their daily roles
Learn how to visualize data and present findings using various charts in Excel spreadsheets and BI tools like IBM Cognos Analytics & Tableau
Develop working knowledge of Python language for analyzing data using Python libraries like Pandas and Numpy, and invoke APIs and Web Services
Gain technical experience through hands on labs and projects and build a portfolio to showcase your work
Add to your LinkedIn profile
Prepare for a career in the high-growth field of data analytics. In this program, you’ll learn in-demand skills like Python, Excel, and SQL to get job-ready in as little as 4 months.
Data analysis is the process of collecting, storing, modeling, and analyzing data that can inform executive decision-making, and the demand for skilled data analysts has never been greater.
This program will teach you the foundational data skills employers are seeking for entry-level data analytics roles. It will not only help you start your career in data analytics, but also provides a strong foundation for future career development in other paths such as data science, artificial intelligence, deep learning, or data engineering.
You’ll learn the latest skills and tools used by professional data analysts including Excel spreadsheets, Python, Pandas, Numpy, Jupyter Notebooks, Cognos Analytics, and more. You’ll work with a variety of data sources and project scenarios to gain practical experience with data manipulation and applying analytical skills. You'll also have the option to learn how generative AI tools and techniques are used in data analysis.
In addition to a portfolio of projects and a Professional Certificate from IBM to showcase your expertise, you’ll earn an IBM Digital badge and gain access to career resources to help you in your job search.
This program is ACE® and FIBAA recommended—when you complete, you can earn up to 12 college credits and 6 ECTS credits.
Applied Learning Project
Throughout the program, you’ll complete hands-on projects and labs and gain a firm grasp on the required technical skills to effectively gather, wrangle, mine, and visualize data, as well as the soft skills for working with stakeholders and storytelling with data to engage your audience.
Projects
Import, clean, and analyze fleet vehicle inventory with Excel pivot tables
Use car sales key performance indicator (KPI) data to create an interactive dashboard with visualizations
Extract and graph financial data with the Pandas data analysis Python library
Use SQL to query census, crime, and school demographic data sets
Wrangle data, graph plots, and create regression models to predict housing prices with data science Python libraries
Create a dynamic Python dashboard to monitor, report, and improve US domestic flight reliability
At the end of the program, you complete a real-world capstone project specifically designed to showcase your newly learned data analyst skills.
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.
Learn Python - the most popular programming language and for Data Science and Software Development.
Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes.
Demonstrate proficiency in using Python libraries such as Pandas & Numpy, and developing code using Jupyter Notebooks.
Access and web scrape data using APIs and Python libraries like Beautiful Soup.
Play the role of a Data Scientist / Data Analyst working on a real project.
Demonstrate your Skills in Python - the language of choice for Data Science and Data Analysis.
Apply Python fundamentals, Python data structures, and working with data in Python.
Build a dashboard using Python and libraries like Pandas, Beautiful Soup and Plotly using Jupyter notebook.
Analyze data within a database using SQL and Python.
Create a relational database and work with multiple tables using DDL commands.
Construct basic to intermediate level SQL queries using DML commands.
Compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins.
Develop Python code for cleaning and preparing data for analysis - including handling missing values, formatting, normalizing, and binning data
Perform exploratory data analysis and apply analytical techniques to real-word datasets using libraries such as Pandas, Numpy and Scipy
Manipulate data using dataframes, summarize data, understand data distribution, perform correlation and create data pipelines
Build and evaluate regression models using machine learning scikit-learn library and use them for prediction and decision making
Implement data visualization techniques and plots using Python libraries, such as Matplotlib, Seaborn, and Folium to tell a stimulating story
Create different types of charts and plots such as line, area, histograms, bar, pie, box, scatter, and bubble
Create advanced visualizations such as waffle charts, word clouds, regression plots, maps with markers, & choropleth maps
Generate interactive dashboards containing scatter, line, bar, bubble, pie, and sunburst charts using the Dash framework and Plotly library
Apply techniques to gather and wrangle data from multiple sources.
Analyze data to identify patterns, trends, and insights through exploratory techniques.
Create visual representations of data using Python libraries to communicate findings effectively.
Construct interactive dashboards with BI tools to present and explore data dynamically.
Describe how you can use Generative AI tools and techniques in the context of data analytics across industries
Implement various data analytic processes such as data preparation, analysis, visualization and storytelling using Generative AI tools
Evaluate real-world case studies showcasing the successful application of Generative AI in deriving meaningful insights
Analyze the ethical considerations and challenges associated with using Generative AI in data analytics
Describe the role of a data analyst and some career path options as well as the prospective opportunities in the field.
Explain how to build a foundation for a job search, including researching job listings, writing a resume, and making a portfolio of work.
Summarize what a candidate can expect during a typical job interview cycle, different types of interviews, and how to prepare for interviews.
Explain how to give an effective interview, including techniques for answering questions and how to make a professional personal presentation.
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
University of London
Degree · 3 – 6 years
University of Maryland Global Campus
Degree · 48 months
Illinois Tech
Degree
University of Maryland Global Campus
Degree · 48 months
O.P. Jindal Global University
Degree · 12 - 24 months
O.P. Jindal Global University
Degree · 24 - 36 months
Illinois Tech
Degree · 12-24 months
Illinois Tech
Degree · 12-15 months
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.
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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The impact of the IBM Data Analyst Professional Certificate on my career and professional growth has been significant. It added credibility to my resume, demonstrated my commitment to continuous learning and professional development, and played a crucial role in helping me secure a job as a professional data analyst.
Learning from Poland
“
The impact of the IBM Data Analyst Professional Certificate on my career and professional growth has been significant. It added credibility to my resume, demonstrated my commitment to continuous learning and professional development, and played a crucial role in helping me secure a job as a professional data analyst.
Learning from Poland
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Data analysis involves gathering, cleaning, organizing, modelling, and visualising data with the goal of extracting helpful insights that can inform decision-making.
Data analytics skills will prove valuable in any profession. As data analytics technology develops, organizations across fields are increasingly using data to inform decision-making. This program will provide you with all the skills needed for an entry-level Data Analyst role, and will provide a strong foundation for future career development in other paths such as data science or data engineering.
This is a self-paced Professional Certificate that you can complete on your own schedule in as little as 5 months.
No specialized background or degree is needed. However you are expected to have basic computer literacy, high-school level mathematics, and be comfortable working with numbers.
It is highly recommended to complete the courses in the order they are listed as they build upon concepts in the previous courses.
Upon completing this Professional Certificate, you will be armed with the skills and knowledge to start an entry level role in data analytics. You can also apply your newly-acquired analytical skills to enrich your current career in a variety of industries including banking, accounting, and IT and functions such as marketing, finance, and research.
Data analytics skills are also valuable as an entry point to other data-related professions such as data science, data engineering, and business analytics.
Yes. The IBM Data Analyst 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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