Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
The Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Course provided by MICA aims at educating learners about the latest trends and developments in the field of marketing management and marketing analytics. The online course is a 6-month specialized programme available on the Eruditus Executive Education platform.
Through the Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Live Course, learners will be introduced to different types of research techniques using data-driven strategies that meet the market requirements. Learners will also be equipped with skills in machine learning applications.
The Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Training Course is delivered through live online sessions, discussion boards, webinars and other interactive sessions with experts in the field. If you successfully complete the evaluations and score 70% overall, you will be rewarded with a certificate from MICA.
The Highlights
- Certificate of completion
- 6 months duration
- 100+ video lectures
- Live online classes
- 10 Discussion boards
- Live webinars with MICA faculty
- 15+ Quizzes and assignments
- Chance to get Executive Alumni Status
Programme Offerings
- Certificate of completion
- 6 months duration
- live online sessions
- video lectures
- Discussion boards
- quizzes
- assignments
- LIVE Webinars
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | MICA, Ahmedabad |
The Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Course fee is Rs. 71,750 + GST. There is an option for candidates to take loans with EMI starting at Rs. 4,055. You can enroll in the course with your co-workers and avail of a special corporate enrolment pricing plan and get up to a 10% discount.
Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Fee Structure
Course | Amount |
Advanced Certificate Programme in Statistics & Analytics for Marketing Insights | Rs. 71,750 + GST |
Eligibility Criteria
The course can be opted by anyone with a graduate or diploma degree (10+2+3) from any discipline.
What you will learn
After learning the Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Classes, you will gain knowledge about the following topics:
- Types of market research
- Overview of business analytics
- Applications and tools of business analytics
- Descriptive statistics
- Data analysis and data visualization
- Summarizing data using Excel and Tableau
- Statistical sampling methods
- Hypothesis testing
- Univariate, bivariate, and multivariate data
- Discriminant analysis and conjoint analysis
- Structural Equation Modelling (SEM)
- Introduction to machine learning
- Time Series Analysis
- Auto Regressive-Moving Average (ARMA)
- Auto-Regressive Integrated Moving Average (ARIMA)
Who it is for
- The Advanced Certificate Programme in Statistics & Analytics for Marketing Insights course is suitable for all professionals who aim to achieve skills in market research and marketing analytics for contributing to effective marketing strategies.
- The course will be beneficial for any professional wanting to adopt analytics-driven solutions rooted in data science to create powerful impacts in the global market.
Admission Details
Follow the steps to enroll in the Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Training Course:
Step 1: Click on the URL given below -https://mica.eruditus.com/advanced-certificate-programme-in-marketing-analytics
Step 2: Click on the “Start Application Now” option at the end of the page.
Step 3: A new tab opens with the application form. Enter your email id and proceed.
The Syllabus
- Introduction to Market Research
- Overview of types of Market Research
- Structure of a Research Report
- Introduction to Business Analytics
- Overview of Business Analytics Tools
- Applications of Analytics in Business
- Introduction to Descriptive Statistics
- Measures of Central Tendency
- Calculating Measures of Central Tendency using Excel
- Measures of Dispersion
- Calculating Measures of Dispersion using Excel
- Measures of Shape
- Calculating Measures of Shape using Excel
- Data Visualisation and its application in Business
- Ways of Data Visualisation
- Data Visualisation Using Different Charts
- Data Analysis Using Filtering
- Data Analysis: Pareto Principle and its Application
- Filtering and Pareto Analysis using Tableau
- Ways of Summarising Data
- Summarizing Data Using Excel and Tableau
- Sample and Population
- Statistical Sampling
- A sampling plan
- Sampling Methods
- Estimating Population Parameters and sampling errors
- Sampling Distributions
- Normal Distribution
- Business Use Cases
- Statistical Inference: Hypothesis Testing
- Z - Test
- T-Test
- One-Sample Hypothesis Tests
- Selecting the Test Statistics
- P - Values
- Drawing a Conclusion Using Hypothesis Testing
- Two-sample Hypothesis Tests
- Two-Sample t-Test for Means: Independent Samples
- Two-Sample t-Test for Means: Paired Samples
- Covariance
- Correlation
- Regression
- Analysis of Variance (One-Way ANOVA)
- Chi-Square Test for independence
- Debrief of the Project
Module 9: Fundamentals of MDA and associated techniques
- Introduction to univariate, bivariate and multivariate data
- MVA techniques: Dependence and interdependence methods
- Introduction to regression: simple linear regression and multiple linear regression
- Measures to evaluation prediction models: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and R Squared (R2)
- Apply linear regression to a dataset and evaluate its accuracy
Module 10: Discriminant Analysis
- Discriminant analysis - introduction
- Discriminant analysis – working: linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA)
- Modelling, Inference, and Evaluation
- Conjoint analysis - introduction, and working
- Modelling, Inference, and Evaluation
Module 11: Inferential Statistics: Sampling and Estimation
- Introduction to PCA
- Modelling, Inference, and Evaluation
Module 12: Structural Equation Modelling (SEM)
- Introduction to SEM (concept and terminologies)
- Working of SEM (measurement model, structural model, metrics for reliability and validity, CB-SEM and PLS-SEM)
- Modelling, Inference, and Evaluation
Module 13: Introduction to Classification
- Introduction to Machine Learning
- Fundamentals of Classification and associated techniques
- Evaluating Classification Models
- Testing, Training, and Validation
- Validation Methods
- Applications in Marketing
Module 14: Logistic Regression and SVM
- Introduction to the model
- Introduction to the data
- Modelling, Inference, and Evaluation
Module 15: Decision Trees and Random Forest
- Introduction to Machine Learning Regression
- Introduction to the model (decision tree, random forest, bagging and boosting)
- Modelling, Inference, and Evaluation
Module 16: Random Forest Regression
- Introduction to Random Forest regression
- Modelling, Inference and Evaluation
Module 17: Boosting and Bagging Regression
- Ensemble learning (parallel and sequential ensemble methods)
- Bagging and boosting
- Modelling, Inference, and Evaluation
Module 18: Fundamentals of Clustering and associated techniques
- Introduction to Unsupervised Learning and Clustering
- Introduction to K-means
- Modelling, Inference, and Evaluation
Module 19: Apriori Algorithm
- Introduction to the Model
- Modelling, Inference, and Evaluation
- Other Clustering methods
Module 20: Introduction to Time Series
- Fundamentals of Time Series Analysis and associated techniques (concept, components of time series, decomposition of time series, autocorrelation function (ACF))
- Naive Model
- Averaging model
- Simple Moving Average
- Exponential Smoothing Methods
Module 21: ARMA and ARIMA
- Stationarity and differencing, ACF and PACF
- AR and MA model
- ARMA (Auto Regressive-Moving Average)
- Introduction to ARIMA, steps in ARIMA modelling, forecasting with ARIMA (Auto-Regressive Integrated Moving Average)
- Final Project
Instructors
MICA, Ahmedabad Frequently Asked Questions (FAQ's)
The Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Training Course has a total duration of 6 months.
Candidates are required to submit their degree certificate, provisional degree certificate marks transcript, or score transcript for applying to the Advanced Certificate Programme in Statistics & Analytics for Marketing Insights course.
Only those who score 70% during the evaluation will be given a course certificate from MICA.
No, the Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Certification Course does not offer its learners any placement opportunities.
The Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Online Course is instructed by Prof. Dharun Kasilingam and Prof. Niyati Bhanja of MICA.