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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video Based |
Course Overview
The Data Analysis for Social Scientists certification course will introduce learners to the fundamentals of statistics, probability, and data analysis. The curriculum covers most modern data analysis techniques including estimation, prediction, regression and econometrics, experimental design, A/B testing, randomized control trials, data visualization, and machine learning.
All these concepts are illustrated using real-world examples. Candidates will also learn how to use the statistical package R, and perform self-directed empirical analyses.
The Data Analysis for Social Scientists certification is also a prerequisite for two independent MicroMasters programs that the Massachusetts Institute of Technology (MIT) offers: MicroMasters in Data, Economics, and Development Policy (DEDP) and MicroMasters in Statistics and Data Science (SDS).
Before you apply to the Data Analysis for Social Scientists program, you check out the course preview to go through the content, exercises, etc. Some resources are also available if you are new to these subjects or wish to jog your memory. If you score 60% or more in the course preview, it indicates that you are prepared for this course.
The Highlights
- Free learning
- MIT programme
- Advanced course
- Eleven-week course
- 12-14 hours in a week
- Video lectures in English
- Course preview available
- Video transcripts in English
- Instructor-led scheduled course
- Prerequisite for the SDS MicroMasters programme
- Prerequisite for the DEDP MicroMasters programme
Programme Offerings
- MIT Programme
- Free learning
- Advanced course
- 12-14 hours in a week
- Eleven-week course
- Course preview available
- Prerequisite for the DEDP MicroMasters program
- Video lectures in English
- Video transcripts in English
- Instructor-led Scheduled Course
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | MIT Cambridge |
Eligibility Criteria
Interested candidates can apply to the Data Analysis for Social Scientists program even if they are not trained in statistics and probability. However, they should be comfortable with algebra and calculus.
What you will learn
Completing the eleven-week Data Analysis for Social Scientists training will help you learn the following:
- Summarising and describing data
- Skills and tools to analyze data using R
- Methods to evaluate social programs
- The intuition behind statistics and probability analysis
- Presenting results in a truthful and compelling way
Who it is for
This Data Analysis for Social Scientists online course will benefit individuals who want to learn how to analyze data and effectively communicate their findings.
Admission Details
Step 1: Join the Data Analysis for Social Scientists course by tapping on this link: https://www.edx.org/course/data-analysis-for-social-scientists
Step 2: Find the "Enrol" tab on the web page to open the online registration page.
Step 3: Sign-up with edX through your social media accounts (Google/ Apple/Microsoft/Facebook). Or else, you can register by creating a new edX learning account.
Step 4: Finally, submit the form and commence learning.
Application Details
Candidates interested in the Data Analysis for Social Scientists program can apply by filling out an online registration form. Provide your contact information in the form, including your name, email address, and country of residence.
The Syllabus
Instructors
MIT Cambridge Frequently Asked Questions (FAQ's)
You can access the course preview and solve the exercises there. If you score 60% or more, you are prepared for the program. If not, you should review the topics covered before you apply.
This course is a prerequisite for two programs: MicroMasters in Data, Economics, and Development Policy (DEDP) and MicroMasters in Statistics and Data Science (SDS).
No. But you must have a working knowledge of algebra and calculus.
No. This program is only provided in an instructor-led mode, with scheduled weekly classes.