Big data means big career opportunities.
The online Data Analytics Certificate Program teaches you how to solve a broad range of problems using a variety of predictive analytics and statistical techniques. Our program focuses on examining the vast amounts of data now generated by organizations and their customers and employees during online transactions, in order to develop informed strategies. It is designed to enhance the ability of professionals from any field to utilize data analytics and big data when making decisions. You will learn to apply statistical machine learning and other techniques to data sets, and you will discover how to collaborate with information technology and other specialists in collecting, maintaining and analyzing data to better inform decisions.
The program provides a 100% project-based, learn-by-doing experience, and while the program is online, you will not be alone. You will work synchronously with a small team of fellow students supported by an expert mentor.
In addition to data analytics and data science training, you will also receive career coaching designed to help you land a job. From mock interviews to resume assistance to portfolio development, your mentor will ensure you have polished interview skills and a digital portfolio that showcases your skills and experience as a data analyst or data scientist.
View short videos of Senior Mentor Ben Manning discussing the curriculum, career support and the mentorship model unique to this program.
- Professionals who want to acquire new skills in the areas of data analytics and big data
- Accounting, IT and engineering professionals
- Marketing professionals
- Anyone who reports on business processes
- Anyone responsible for benchmarking or strategy development
- Learn to apply Python, R, R Studio, SQL, Spark, NLP, Supervised Machine Learning, Amazon Web Services and more to data analytics and data science problems.
- Translate business objectives into data mining opportunities and implement predictive analytics solutions to address business objectives.
- Install, run and apply statistical machine learning tools on classification and regression problems involving structured and unstructured data.
- Acquire, process and analyze large data sets using cloud-based data mining methods for data exploration, pattern discovery, prediction and answering business questions.
- Develop the confidence to succeed as a data analyst/data scientist by building a professional portfolio that includes end-to-end project experience on practical data analytics/data science projects.
- PC, Mac or Linux desktop or laptop computer
- 8 GB of Ram, minimum. 16 GB of Ram recommended
- Intel or compatible processor
- 500 GB hard drive (minimum)
- Operating System: (Windows, Mac OS or Linux; most recent OS versions recommended)
- High-speed internet connection
- Current version of Microsoft Office or Microsoft Office for Mac (Open Office or Libre Office may also be used)
- HD webcam for videoconferencing (a laptop webcam is sufficient)
Applicants are required to have:
- Two years of work experience
- Familiarity with Windows, Mac or Linux operating system, specifically:
- Creating and managing folders within folders
- Creating and extracting files from zip archives
- Elementary administrative tasks (e.g., installing software requiring admin privileges)
- Basic familiarity with Microsoft Office or an equivalent productivity suite
Previous knowledge of statistics is helpful, but not required.
Please note there is some recommended pre-work for the Data Analytics program which will be emailed to you in advance of the class start date.
Rather than provide a step-by-step instruction style, our program will call for you to engage in self-directed learning. If you do not already have those self-directed learning skills, this course will help you to develop them by encouraging you to track down the answers to questions, instead of depending on an instructor to provide the answer.
1. There is a significant time commitment difference between the full-time and part-time program. On average, students should plan to commit at least 30 hours per week for the full-time program and at least 15 hours per week for the part-time program. For optimal success, it is recommended that students with full-time employment enroll in the part-time program.
2. This course is offered in collaboration with XTOL.
3. Find additional information about optional career services.
Interested students may be eligible to apply for the Road to Success Scholarship, which could cover up to 80% of this program's tuition.