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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

Marketing skillsMachine learningData science knowledgeBusiness analytics knowledgeKnowledge of Data Visualization

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)

1: What is the duration of the Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Course?

The Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Training Course has a total duration of 6 months.

2: What all documents are required for applying for the Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Course?

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.

3: Will all learners in the Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Live Course get a certificate?

Only those who score 70% during the evaluation will be given a course certificate from MICA.

4: Will I get a job through placement via this Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Live Course?

No, the Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Certification Course does not offer its learners any placement opportunities.

5: Who are the Advanced Certificate Programme in Statistics & Analytics for Marketing Insights course instructors?

The Advanced Certificate Programme in Statistics & Analytics for Marketing Insights Online Course is instructed by Prof. Dharun Kasilingam and Prof. Niyati Bhanja of MICA.