IBM Data Analyst Certificate Online
Ready yourself for a career in big data analytics with IBM data analyst courses that teach you to develop professional data-driven solutions using data analytics tools like Python.
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LEARN MOREWhat You Will Learn
- Learn the fundamentals of data analytics fundamentals and examine the tools data analysts use to clean, analyze and share data
- Develop proficiency with Excel spreadsheets, including how and when to use Excel as a data analysis tool
- Explore how data is used to tell a story, then develop your own data visualizations and interactive dashboards using IBM Cognos Analytics and Excel
- Discover data manipulation techniques and gain a thorough working knowledge of databases, SQL and Python
About the IBM Data Analyst Professional Certificate
If you're a detail-oriented person who likes to delve into the meaning behind things, and you're looking for a growth-oriented career, this IBM Data Analyst Professional Certificate is for you.
Featuring nine courses developed by IBM, this certificate program is designed to equip you with the fundamental skills needed to work in data analytics. Data analytics is a growing specialty, which means the demand for analysts is high. And, with an anticipated 20% growth rate over the next 5 years, demand is getting even higher.
With this Professional Certificate program, you can study at your own pace as you learn to analyze datasets, create interactive dashboards, and visualize data. You'll develop technical expertise with some of today's most popular analytics tools and data sources, too, including Excel, SQL, Cognos and Python.
Plus, you'll get hands-on practice in data analytics, thanks to applied learning assignments and a capstone project -- all of which you can use to create a portfolio that showcases your skills and capabilities as a data analyst.
Required IBM Data Analyst Certificate Courses
BEGINNER | Data Science | Self-paced | 11 hours
Ready to start a career in Data Analysis but don’t know where to begin? This course presents you with a gentle introduction to Data Analysis, the role of a Data Analyst, and the tools used in this job. You will learn about the skills and responsibilities of a data analyst and hear from several data experts sharing their tips & advice to start a career. This course will help you to differentiate between the roles of Data Analysts, Data Scientists, and Data Engineers. You will familiarize yourself with the data ecosystem, alongside Databases, Data Warehouses, Data Marts, Data Lakes and Data Pipelines. Continue this exciting journey and discover Big Data platforms such as Hadoop, Hive, and Spark. By the end of this course you’ll be able to understand the fundamentals of the data analysis process including gathering, cleaning, analyzing and sharing data and communicating your insights with the use of visualizations and dashboard tools. This all comes together in the final project where it will test your knowledge of the course material, and provide a real-world scenario of data analysis tasks. This course does not require any prior data analysis, spreadsheet, or computer science experience.
BEGINNER | Data Science | Self-paced | 12 hours
Spreadsheet tools like Excel are an essential tool for working with data - whether for data analytics, business, marketing, or research. This course is designed to give you a basic working knowledge of Excel and how to use it for analyzing data. This course is suitable for those who are interested in pursuing a career in data analysis or data science, as well as anyone looking to use Excel for data analysis in their own domain. No prior experience with spreadsheets or coding is required - all you need is a device with a modern web browser and the ability to create a Microsoft account to access Excel online at no cost. If you have a desktop version of Excel, you can also easily follow along with the course. Throughout this course, you'll gain valuable experience working with data sets and spreadsheets. We'll start by introducing you to spreadsheets like Microsoft Excel and Google Sheets, and show you how to load data from multiple formats. From there, you'll learn how to perform basic data wrangling and cleansing tasks using functions, and expand your knowledge of data analysis through the use of filtering, sorting, and pivot tables. There is a strong focus on practice and applied learning in this course. With each lab, you'll have the opportunity to manipulate data and gain hands-on experience using Excel. You'll learn how to clean and format your data efficiently, and convert it into a pivot table to make it more organized and readable. The final project will allow you to showcase your newly acquired data analysis skills by working with real data sets and spreadsheets. By the end of this course, you'll have a solid foundation in using Excel for data analysis. You'll have worked with multiple data sets and spreadsheets, and will have the skills and knowledge needed to effectively clean and analyze data without having to learn any code. So let's get started!
BEGINNER | Data Science | Self-paced | 15 hours
Learn how to create data visualizations and dashboards using spreadsheets and analytics tools. This course covers some of the first steps for telling a compelling story with your data using various types of charts and graphs. You'll learn the basics of visualizing data with Excel and IBM Cognos Analytics without having to write any code. You'll start by creating simple charts in Excel such as line, pie and bar charts. You will then create more advanced visualizations with Treemaps, Scatter Charts, Histograms, Filled Map Charts, and Sparklines. Next you’ll also work with the Excel PivotChart feature as well as assemble several visualizations in an Excel dashboard. This course also teaches you how to use business intelligence (BI) tools like Cognos Analytics to create interactive dashboards. By the end of the course you will have an appreciation for the key role that data visualizations play in communicating your data analysis findings, and the ability to effectively create them. Throughout this course there will be numerous hands-on labs to help you develop practical experience for working with Excel and Cognos. There is also a final project in which you’ll create a set of data visualizations and an interactive dashboard to add to your portfolio, which you can share with peers, professional communities or prospective employers.
BEGINNER | Data Science | Self-paced | 49 hours
Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher. This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types. You will familiarize yourself with Python Data structures like List and Tuples, as well as logic concepts like conditions and branching. You will use Python libraries such as Pandas, Numpy & Beautiful Soup. You’ll also use Python to perform tasks such as data collection and web scraping with APIs. You will practice and apply what you learn through hands-on labs using Jupyter Notebooks. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python. This course is suitable for anyone who wants to learn Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps as well as a number of other job roles.
INTERMEDIATE | Data Science | Self-paced | 9 hours
This mini-course is intended to for you to demonstrate foundational Python skills for working with data. This course primarily involves completing a project in which you will assume the role of a Data Scientist or a Data Analyst and be provided with a real-world data set and a real-world inspired scenario to identify patterns and trends. You will perform specific data science and data analytics tasks such as extracting data, web scraping, visualizing data and creating a dashboard. This project will showcase your proficiency with Python and using libraries such as Pandas and Beautiful Soup within a Jupyter Notebook. Upon completion you will have an impressive project to add to your job portfolio. PRE-REQUISITE: **Python for Data Science, AI and Development** course from IBM is a pre-requisite for this project course. Please ensure that before taking this course you have either completed the Python for Data Science, AI and Development course from IBM or have equivalent proficiency in working with Python and data. NOTE: This course is not intended to teach you Python and does not have too much instructional content. It is intended for you to apply prior Python knowledge.
BEGINNER | Data Science | Self-paced | 20 hours
Working knowledge of SQL (or Structured Query Language) is a must for data professionals like Data Scientists, Data Analysts and Data Engineers. Much of the world's data resides in databases. SQL is a powerful language used for communicating with and extracting data from databases. In this course you will learn SQL inside out- from the very basics of Select statements to advanced concepts like JOINs. You will: -write foundational SQL statements like: SELECT, INSERT, UPDATE, and DELETE -filter result sets, use WHERE, COUNT, DISTINCT, and LIMIT clauses -differentiate between DML & DDL -CREATE, ALTER, DROP and load tables -use string patterns and ranges; ORDER and GROUP result sets, and built-in database functions -build sub-queries and query data from multiple tables -access databases as a data scientist using Jupyter notebooks with SQL and Python -work with advanced concepts like Stored Procedures, Views, ACID Transactions, Inner & Outer JOINs through hands-on labs and projects You will practice building SQL queries, work with real databases on the Cloud, and use real data science tools. In the final project you’ll analyze multiple real-world datasets to demonstrate your skills.
INTERMEDIATE | Data Science | Self-paced | 15 hours
Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
INTERMEDIATE | Data Science | Self-paced | 20 hours
One of the most important skills of successful data scientists and data analysts is the ability to tell a compelling story by visualizing data and findings in an approachable and stimulating way. In this course you will learn many ways to effectively visualize both small and large-scale data. You will be able to take data that at first glance has little meaning and present that data in a form that conveys insights. This course will teach you to work with many Data Visualization tools and techniques. You will learn to create various types of basic and advanced graphs and charts like: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps, and many more! You will also create interactive dashboards that allow even those without any Data Science experience to better understand data, and make more effective and informed decisions. You will learn hands-on by completing numerous labs and a final project to practice and apply the many aspects and techniques of Data Visualization using Jupyter Notebooks and a Cloud-based IDE. You will use several data visualization libraries in Python, including Matplotlib, Seaborn, Folium, Plotly & Dash.
INTERMEDIATE | Data Science | Self-paced | 18 hours
By completing this final capstone project you will apply various Data Analytics skills and techniques that you have learned as part of the previous courses in the IBM Data Analyst Professional Certificate. You will assume the role of an Associate Data Analyst who has recently joined the organization and be presented with a business challenge that requires data analysis to be performed on real-world datasets. You will perform the various tasks that professional data analysts do as part of their jobs, including: - Data collection from multiple sources - Data wrangling and data preparation - Exploratory data analysis - Statistical analysis and data mining - Data visualization with different charts and plots, and - Interactive dashboard creation. The project will culminate with a presentation of your data analysis report for various stakeholders in the organization. The report will include an executive summary, your analysis, and a conclusion. You will be assessed on both your work for the various stages in the Data Analysis process, as well as the final deliverable. As part of this project you will demonstrate your proficiency with using Jupyter Notebooks, SQL, Relational Databases (RDBMS), Business Intelligence (BI) tools like Cognos, and Python Libraries such as Pandas, Numpy, Scikit-learn, Scipy, Matplotlib, Seaborn and others. This project is a great addition to your portfolio and an opportunity to showcase your Data Analytics skills to prospective employers.
INTERMEDIATE | Data Science | Self-paced | 14 hours
This comprehensive course unravels the potential of generative AI in data analytics. The course will provide an in-depth knowledge of the fundamental concepts, models, tools, and generative AI applications regarding the data analytics landscape. In this course, you will examine real-world applications and use generative AI to gain data insights using techniques such as prompts, visualization, storytelling, querying and so on. In addition, you will understand the ethical implications, considerations, and challenges of using generative AI in data analytics across different industries. You will acquire practical experience through hands-on labs where you will leverage generative AI models and tools such as ChatGPT, ChatCSV, Mostly.AI, SQLthroughAI and more. Finally, you will apply the concepts learned throughout the course to a data analytics project. Also, you will have an opportunity to test your knowledge with practice and graded quizzes and earn a certificate. This course is suitable for both practicing data analysts as well as learners aspiring to start a career in data analytics. It requires some basic knowledge of data analytics, prompt engineering, Python programming and generative artificial intelligence.
BEGINNER | Data Science | Self-paced | 10 hours
Data analytics professionals are in high demand around the world, and the trend shows no sign of slowing. There are lots of great jobs available, but lots of great candidates too. How can you get the edge in such a competitive field? This course will prepare you to enter the job market as a great candidate for a data analyst position. It provides practical techniques for creating essential job-seeking materials such as a resume and a portfolio, as well as auxiliary tools like a cover letter and an elevator pitch. You will learn how to find and assess prospective job positions, apply to them, and lay the groundwork for interviewing. The course doesn’t stop there, however. You will also get inside tips and steps you can use to perform professionally and effectively at interviews. You will learn how to approach a take-home challenges and get to practice completing them. Additionally, it provides information about the regular functions and tasks of data analysts, as well as the opportunities of the profession and some options for career development. You will get guidance from a number of experts in the data industry through the course. They will discuss their own career paths and talk about what they have learned about networking, interviewing, solving coding problems, and fielding other questions you may encounter as a candidate. Let seasoned data analysis professionals share their experience to help you get ahead and land the job you want.Complete This Certificate. Get College Credit.
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Frequently Asked Questions
When you enroll in this self-paced certificate program, you decide how quickly you want to complete each of the courses in the specialization. To access the courses, you pay a small monthly cost of $35, so the total cost of your Professional Certificate depends on you. Plus, you can take a break or cancel your subscription anytime.
It takes about 4-5 months to finish all the courses and hands-on projects to earn your certificate.
No prior experienced is needed for this beginner-level series, however, you'll need to have basic computer skills and be comfortable working with numbers.
Share your certificate with your professional network and anyone looking to hire an entry-level data analyst. Your certificate is demonstrated proof of your data analytics, DataViz and data science qualifications.
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Please submit your certificate to plc@franklin.edu for review and processing. After your official evaluation has been completed, please review it to ensure that all eligible credits have been applied.
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