Individuals who have a basic science and analysis background. It is best suited for those with the capability of leveraging applied science with python and other similar computing languages. Participants should be able to utilize these skill sets to conduct data analysis and generate data visualization reports based on different business scenarios.
Steps to take exam
- Visit our certification page: https://www.ideassn.org/certificate/
- Register at ideas for purchasing certification. (If you already have an account, you can skip this step)
- Purchase the certification test you want to take.
- During your purchasing process, please clarify the time at which you want to take the exam in ADDITIONAL INFORMATION BOX. (the duration should no longer than 1 MONTH)
- For example, you can write: 2/2/2019-3/2/2019, then you will receive a link which is continuously activated during this time, and you can pick any time to start your exam.
- The system will send you a confirmation mail once you finish the order
- After the order confirmation, you will get the link via email to access the test (the link is activated during your preferred test duration.)
- This certification test could be taken anytime and anywhere, but you may only take it once, and the time duration for the exam is 2hr.
Pass the Test and Get Certification
- You will receive your grade via email within 1 week of submitting your test.
- You need to get at least 90% to pass this test.
- Congratulations! You will get our certification if you pass the test.
Exam duration – 2 hour
- 1 hour technical questions
- 1 hour project challenge
Basic Theory: Statistics, Probability, Data Mining, Basic Python Programming, Data Processing, Data Visualization, Machine Learning
Tools and Software Requirements: Python
Prerequisite Skills: Ability to utilize python and similar tools to generate data visualization reports through implementing data control, data processing, data cleaning, analysis and related tasks.
- Foundations of Numpy and Panda
- Data Manipulation
- Data Visualization
- Basic Machine Learning (Linear Regression, Logistic Regression, Decision Tree, Random Forest…)