Frequently Asked Questions
The answer to this question depends upon what each person is attempting to achieve. This certification program is designed to teach people the fundamentals of data analytics. We've included courses that enable people to acquire the knowledge and skills that support the management and use of big data. Students learn how to ask the right questions, make inferences, apply what they've learned immediately to real-world situations, and publish results. The certification may enable you to obtain a new job working in data analytics, but we recommend that you search the requirements for data scientist positions to learn what qualifications individual employers are seeking. Typically, companies require a degree in data analytics and/or several years of experience working in this field. The Ohio State University offers bachelor's and master's degrees in data analytics for people who may want to pursue this type of education. But this program is a great way for people to gain the fundamental working knowledge of the data analytics pipeline so they can use these skills in their current occupation. What a person can achieve after that with the new skill-set really depends upon many other factors and what type of career change a person may be seeking.
Yes. Students receive a certificate after completing each course. And a final certificate stating completion of the certification.
No. Final course grades are Pass/Fail based on an 80% or better score.
Yes. It is required that students take Introductory Statistics for Data Analytics first, followed by Data Mining, then Applied Machine Learning, followed by Neural Networks and Deep Learning. Visual Analytics can be taken at any time.
No there is no application process. The registration includes typically required information only such as name, address, phone, etc.
No. This certification is non-credit, therefore the courses will not appear on an official Ohio State University transcript.
No. This certification is non-credit so it's not possible.
Yes. If you believe that you have the necessary preparation in statistics, you are not required to take the Introductory Statistics for Data Analytics course. Students who successfully complete three other courses can still obtain the certification. But the faculty in the other courses are not responsible to teach students statistics, so please make sure you are prepared. If it has been a long time since you had a course in statistics, we strongly recommend that you take Introductory Statistics for Data Analytics to refresh yourself. Students must also know how to use R Software in this program, so if you have no experience, it's recommended that you complete our Introductory Statistics for Data Analytics course.
Each course is equivalent to a one-semester credit hour class. Therefore each class consists of approximately 40 hours of class time, including 12-13 hours of recorded faculty lectures and 23-24 hours of additional course work. Each course is seven weeks in length, so each week there are 5.7 hours of combined class time (40 hrs / 7 weeks). The average student should allow a 2:1 study-to-class-time ratio to complete the course. This means you should plan to study for two hours for each hour of class time. This equates to 11-12 hours each week to complete all coursework. (5.7 hrs X 2 = 11-12 hrs). Based on a person's own personal strengths and experience, you should increase or decrease the ratio.
Yes. The only exception is for medical-related emergencies and documentation must be provided to the program. An administrative fee will still be imposed to retake the course.
No. Unfortunately, because the courses are non-credit, you must pay for the coursework or your employer/department may offer to pay for the coursework but we can't accept tuition benefits from OSU or financial aid.
Students can select their own pace and take up to a maximum of 3 years to complete the certification.
No. Students pay for one course at a time.
Yes, but it is not recommended due to the time commitment required for completing each course. Each course is equivalent to a one-semester credit hour class. Therefore each class consists of approximately 40 hours of class time, including 12-13 hours of recorded faculty lectures and 23-24 hours of additional course work. Each course is seven weeks in length, so each week there are 5.7 hours of combined class time (40 hrs / 7 weeks). The average student should allow a 2:1 study-to-class-time ratio to complete the course. This means you should plan to study two hours for each hour of class time. This equates to 11-12 hours each week to complete all coursework. (5.7 hrs X 2 = 11-12 hrs). Based on a person's own personal strengths and experience, you should increase or decrease the ratio.
The CPDA referral program offers an opportunity for actively enrolled Certification in Practice of Data Analytics students to save money on future registrations themselves by referring people to the program. When a friend or colleague registers and pays for their first course, they must state who referred them to the program. We will contact the referring person and let them know they're eligible for a $25 discount on their next registration. For each referral, a person is provided a one-use discount code to use with the course registration of their choice. These discounts are stackable so the more referrals you make the more you save. Referral students must be new to the CPDA program and have not taken any other CPDA courses. Discount codes are not transferable. One discount code per referral.