Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The course of inferring causal effects from the observational data offered by the platform of Coursera is free of cost course. The enrolled candidate can get a certificate for this course after paying a fixed amount according to the guidelines of the Coursera platform. The duration for this course is 5 weeks. This course is taught under the guidance of experts from the University of Pennsylvania. The E-certificate is available after the completion of this course.

The enrolled candidates will be provided with all the quizzes, assignments, video lectures, web links for books and references. As this course is free of cost and online, it is easily accessible for all the sections of society. Financial aid is also provided. The course of inferring causal effects from the observational data is highly recommended for all the students, teachers and researchers who are interested in this field. Financial aid is also available for all learners who cannot afford the fee. Total 33 percent of people started a new career after completing this course and 29 percent of them got career benefits after pursuing this course.

The Highlights

100 percent online course
Free of cost course
E-certificate available by Coursera
Financial aid available
Easily shareable e-certificate to various platforms
Flexible deadlines
Intermediate level of learning
The course is taught in English
Instructor for the course is Jason A.Roy from the University of Pennsylvania

Programme Offerings

Online study
Books
references
video lectures

Courses and Certificate Fees

Fees Informations	Certificate Availability	Certificate Providing Authority
INR 2480	yes	Coursera

The fees for the A Crash Course in Causality Inferring Causal Effects from Observational Data course is :

Head	Amount
Programme Fee	Nil
Certificate fee	Rs. 2,480/-

Eligibility Criteria

Certification qualifying details

The course of inferring causal effects from observational data offered by the platform of coursera is absolutely free of cost course. The enrolled will get a certificate after paying Rs 1000 as a registration fee for the examination procedure. Financial aid is available for the students who cannot afford the fee which makes this course unique and beneficial.

What you will learn

Statistical skills

After successful completion of the course of inferring causal effects from observational data candidate will gain important insights on-

Express assumptions with causal graphs
Implement several types of causal inference methods [eg- matching, instrumental variables, inverse probability of treatment weighting]
Identify which causal assumptions are necessary for each type of statistical method
Describe the difference between associations and causation
Define causal effects using potential outcomes

Who it is for

Data ScientistIT EngineerData Engineer

This programme is highly recommended if you are interested in the fields of data and statistics.

This programme is beneficial for the following-
Aspirants who want to start or restart their careers in this field.
Students, creator, researchers, professionals who want to gain knowledge of the field.
Professionals who want to increase their development through their promotions, salary increase.

Admission Details

Candidates who are willing to be a part of this programme must follow the steps that are given below:

Step 1: Visit the Coursera website.

Step 2: Click on the URL https://www.coursera.org/learn/crash-course-in-causality

Step 3: Click on the course you want to enrol yourself into.

Step 4: Fill in your adequate details.

Step 5: After successfully filling the details you can avail the lectures.

The Syllabus

Videos

Welcome to "A Crash Course in Causality"
Confusion over causality
Potential outcomes and counterfactuals
Hypothetical interventions
Causal effects
Causal assumptions
Stratification
Incident user and active comparator designs

Assignments

Practice Quiz
Practice Quiz
Causal effects

Videos

Confounding
Causal graphs
Relationship between DAGs and probability distributions
Paths and associations
Conditional independence (d-separation)
Confounding revisited
Backdoor path criterion
Disjunctive cause criterion

Assignments

Practice Quiz
Identify from DAGs sufficient sets of confounders

Videos

Observational studies
Overview of matching
Matching directly on confounders
Greedy (nearest-neighbor) matching
Optimal matching
Assessing balance
Analyzing data after matching
Sensitivity analysis
Data example in R
Propensity scores
Propensity score matching
Propensity score matching in R

Assignments

Practice Quiz
Practice Quiz
Matching
Propensity score matching
Data analysis project - analyze data in R using propensity score matching

Videos

Intuition for Inverse Probability of Treatment Weighting (IPTW)
More intuition for IPTW estimation
Marginal structural models
IPTW estimation
Assessing balance
Distribution of weights
Remedies for large weights
Doubly robust estimators
Data example in R

Assignments

Practice Quiz
IPTW
Data analysis project - carry out an IPTW causal analysis

Videos

Introduction to instrumental variables
Randomized trials with noncompliance
Compliance classes
Assumptions
Causal effect identification and estimation
IVs in observational studies
Two stage least squares
Weak instruments
IV analysis in R

Assignments

Practice Quiz
Practice Quiz
Instrumental variables / Causal effects in randomized trials with non-compliance

Evaluation process

This course is free of cost, however, enrolled candidates can achieve certification for this course after paying a registration fee of Rs 1000 for the examination procedures. Financial aid is available for students who cannot afford the fee.