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Machine Learning Basics for a Newbie
6 Steps of Machine learning Lifecycle Introduction to Predictive Modeling
Introduction to Exploratory Data Analysis & Data Insights Descriptive Statistics Inferential Statistics How to Understand Population Distributions?
Reading Data Files into Python Different Variable Datatypes
Probability for Data Science Basic Concepts of Probability Axioms of Probability Conditional Probability
Central Tendencies for Continuous Variables Spread of Data KDE plots for Continuous Variable Overview of Distribution for Continuous variables Normal Distribution Skewed Distribution Skeweness and Kurtosis Distribution for Continuous Variable
Central Tendencies for Categorical Variables Understanding Discrete Distributions Performing EDA on Categorical Variables
Dealing with Missing Values Understanding Outliers Identifying Outliers in Data Outlier Detection in Python Outliers Detection Using IQR, Z-score, LOF and DBSCAN
Sample and Population Central Limit Theorem Confidence Interval and Margin of Error
Bivariate Analysis Introduction
Covariance Pearson Correlation Spearman's Correlation & Kendall's Tau Correlation versus Causation Tabular and Graphical methods for Bivariate Analysis Performing Bivariate Analysis on Continuous-Continuous Variables
Tabular and Graphical methods for Continuous-Categorical Variables Introduction to Hypothesis Testing P-value Two sample Z-test T-test T-test vs Z-test Performing Bivariate Analysis on Continuous-Catagorical variables
Chi-Squares Test Bivariate Analysis on Categorical Categorical Variables
Multivariate Analysis A Comprehensive Guide to Data Exploration The Data Science behind IPL
Supervised Learning vs Unsupervised Learning Reinforcement Learning Generative and Descriminative Models Parametric and Non Parametric model
Machine Learning Pipeline Preparing Dataset Build a Benchmark Model: Regression Build a Benchmark Model: Classification
Evaluation Metrics for Machine Learning Everyone should know Confusion Matrix Accuracy Precision and Recall AUC-ROC Log Loss R2 and Adjusted R2
Dealing with Missing Values Replacing Missing Values Imputing Missing Values in Data Working with Categorical Variables Working with Outliers Preprocessing Data for Model Building
Understanding Cost Function Understanding Gradient Descent Math Behind Gradient Descent Assumptions of Linear Regression Implement Linear Regression from Scratch Train Linear Regression in Python Implementing Linear Regression in R Diagnosing Residual Plots in Linear Regression Models Generalized Linear Models Introduction to Logistic Regression Odds Ratio Implementing Logistic Regression from Scratch Introduction to Scikit-learn in Python Train Logistic Regression in python Multiclass using Logistic Regression How to use Multinomial and Ordinal Logistic Regression in R ? Challenges with Linear Regression Introduction to Regularisation Implementing Regularisation Ridge Regression Lasso Regression
Introduction to K Nearest Neighbours Determining the Right Value of K in KNN Implement KNN from Scratch Implement KNN in Python
Bias Variance Tradeoff Introduction to Overfitting and Underfitting Visualizing Overfitting and Underfitting Selecting the Right Model What is Validation? Hold-Out Validation Understanding K Fold Cross Validation
Introduction to Feature Selection Feature Selection Algorithms Missing Value Ratio Low Variance Filter High Correlation Filter Backward Feature Elimination Forward Feature Selection Implement Feature Selection in Python Implement Feature Selection in R
Introduction to Decision Tree Purity in Decision Tree Terminologies Related to Decision Tree How to Select Best Split Point in Decision Tree? Chi-Squares Information Gain Reduction in Variance Optimizing Performance of Decision Tree Train Decision Tree using Scikit Learn Pruning of Decision Trees
Introduction to Feature Engineering Feature Transformation Feature Scaling Feature Engineering Frequency Encoding Automated Feature Engineering: Feature Tools
Introduction to Naive Bayes Conditional Probability and Bayes Theorem Introduction to Bayesian Adjustment Rating: The Incredible Concept Behind Online Ratings! Working of Naive Bayes Math behind Naive Bayes Types of Naive Bayes Implementation of Naive Bayes
Understanding how to solve Multiclass and Multilabled Classification Problem Evaluation Metrics: Multi Class Classification
Introduction to Ensemble Techniques Basic Ensemble Techniques Implementing Basic Ensemble Techniques Finding Optimal Weights of Ensemble Learner using Neural Network Why Ensemble Models Work well?
Introduction to Stacking Implementing Stacking Variants of Stacking Implementing Variants of Stacking Introduction to Blending Bootstrap Sampling Introduction to Random Sampling Hyper-parameters of Random Forest Implementing Random Forest Out-of-Bag (OOB) Score in the Random Forest IPL Team Win Prediction Project Using Machine Learning Introduction to Boosting Gradient Boosting Algorithm Math behind GBM Implementing GBM in python Regularized Greedy Forests Extreme Gradient Boosting Implementing XGBM in python Tuning Hyperparameters of XGBoost in Python Implement XGBM in R/H2O Adaptive Boosting Implementing Adaptive Boosing LightGBM Implementing LightGBM in Python Catboost Implementing Catboost in Python
Different Hyperparameter Tuning methods Implementing Different Hyperparameter Tuning methods GridsearchCV RandomizedsearchCV Bayesian Optimization for Hyperparameter Tuning Hyperopt
Understanding SVM Algorithm SVM Kernels In-depth Intuition and Practical Implementation SVM Kernel Tricks Kernels and Hyperparameters in SVM Implementing SVM from Scratch in Python and R
Introduction to Principal Component Analysis Steps to Perform Principal Compound Analysis Computation of Covariance Matrix Finding Eigenvectors and Eigenvalues Implementing PCA in python Visualizing PCA A Brief Introduction to Linear Discriminant Analysis Introduction to Factor Analysis
Introduction to Clustering Applications of Clustering Evaluation Metrics for Clustering Understanding K-Means Implementation of K-Means in Python Implementation of K-Means in R Choosing Right Value for K Profiling Market Segments using K-Means Clustering Hierarchical Clustering Implementation of Hierarchial Clustering DBSCAN Defining Similarity between clusters Build Better and Accurate Clusters with Gaussian Mixture Models
Understand Basics of Recommendation Engine with Case Study
8 Ways to Improve Accuracy of Machine Learning Models
Introduction to Dask Working with CuML
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to AutoML Implementation of MLBox Introduction to PyCaret TPOT Auto-Sklearn EvalML
Pickle and Joblib Introduction to Model Deployment
Deploying Machine Learning Model using Streamlit Deploying ML Models in Docker Deploy Using Streamlit Deploy on Heroku Deploy Using Netlify Introduction to Amazon Sagemaker Setting up Amazon SageMaker Using SageMaker Endpoint to Generate Inference Deploy on Microsoft Azure Cloud Introduction to Flask for Model Deploying ML model using Flask
Model Deployment in Android Model Deployment in Iphone

Advanced analytics certifications in India

Kunal Jain
Kunal Jain Last Updated : 07 Jan, 2019
3 min read

One question a lot of MIS professionals face day to day is:

“How do I shift my career to work in Advanced Analytics?”

A lot of people have asked this question to me. While there was no clear path for this around 3 years back, the scenario has changed today. Currently, professionals in MIS industry can undertake various certifications in advanced analytics to jump start their analytics career. This article summarizes various certifications available to people in India and rank orders them based on their merits.

Consideration set

This analysis is aimed for people with work experience. I plan to write a similar article for freshers some time later. Further, I have only considered courses from educational institutes well known across India. I have excluded certifications from Software companies (as they tend to focus on software training rather than the concepts behind) and other smaller training institutes.

Following table summarizes various certification options available as of today:

analytics_certificate

Note: There are courses running currently in IIM Bangalore and IIM Lucknow as well, but I am not sure whether they will continue as there is no information on websites of these institutes.

Following are details for each of the courses with link to their websites:

Certificate Programme in Business Analytics (CBA), ISB

The program is a combination of classroom and Technology aided learning platform. Participants will typically be on campus for a 5 day schedule of classroom learning every alternate month for a span of 12 months, which would ideally be planned to include a weekend.
In the month of no classroom connect, the classes will be conducted over a technology aided learning platform. The contact hours in this platform would be 24 hours a month and every alternate month. One more highlight of the programme is the Action learning project whose runs for 3- 6 months and asks students to solve a real business problem from an organization. For more information, go to:

http://www.isb.edu/certificate-programme-in-business-analytics

Advanced Certificate Program in Business Analytics (ACPBA), SJMSOM, IIT Bombay

Jointly designed by the Shailesh J Mehta School Of Management at IIT Bombay, and HughesNet Global Education, the program is spread over one year and covers both the theoretical and practical aspects of the discipline. Industry experts also contribute to the course by giving lectures and presenting real-life consultancy projects. Towards the end of the course, there is 3 day on campus interaction between students and experts. For more information, go to:

http://www.hugheseducation.com/ACPBA

Executive Program in Business Analytics, IIM Calcutta

Again designed with HughesNet Global education, this executive long distance program is designed to expose participants to state of the art tools and techniques of analytics. The program coverage would include discussion on topics such as Data Mining, Design of Experiments, Survey Sampling, Statistical Inference, Investment Management, Financial Modeling, Advanced marketing Research etc.

There are 2 sessions of 3 hour interaction every week (Thursday and Saturday). For more information, go to:

http://www.hugheseducation.com/EPBA

Advanced Business Analytics & Optimization Program (Two Certifications), CEP, IIT Delhi

This program is designed by Ivory education along with DMS, IIT Delhi. It is designed to build Advanced Skills in Business Analytics and Optimization and is divided in two parts. It follows a step-by-step approach where theoretical concepts will be followed by case studies and practical implementations.

http://www.ivoryeducation.com/dms-iit-delhi-advanced-business-analytics-business-optimization-program/

 

Verdict

 So what would I do if I was a MIS professional?

If I had 4 – 5 years of experience and the resources, I would go for the course offered by ISB. There are some clear benefits of this course:

  • You get ISB brand on your CV
  • Method of teaching is mostly classroom, there by giving a lot better learning experience
  • They require higher work experience than most other courses, so you can expect to learn lot more

If I had lesser work experience (resources could still be figured through education loans), I would go for the course run by IIM Calcutta because of more time spent to cover similar course material. Hopefully, this would mean that you have more time for interaction and hands on experience.

So, following is the summary of my recommendations for advanced analytics certification:

analytics_certificate2

Which one would you join if you were a MIS professional? Also, If you are aware of any certification programmes, which could be helpful, please feel free to mention in comments or to write to me.

P.S. All views mentioned here are my own and are in no way biased or influenced by any of the institutes above.

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Kunal Jain
Kunal Jain

Kunal Jain is the Founder and CEO of Analytics Vidhya, one of the world's leading communities of Al professionals. With over 17 years of experience in the field, Kunal has been instrumental in shaping the global Al landscape. His expertise spans diverse markets, from developed economies like the UK to emerging ones like India, where he has successfully led and delivered complex data-driven solutions. As a recognized thought leader, Kunal has empowered countless individuals to realize their Al ambitions through his visionary approach to Al education and community building. Before founding Analytics Vidhya, Kunal earned both his undergraduate and postgraduate degrees from IIT Bombay and held key roles at Capital One and Aviva Life Insurance across multiple geographies. His passion lies at the intersection of analytics, Al, and fostering a thriving community of data science professionals.

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Responses From Readers

Clear

Deepak Rai
Deepak Rai

Hi Kunal, IIM Ranchi has also launched Executive Programme in Business Analytics & Business Intelligence, its a full day class room training spread over few weekends and 5 days training in IIM Ranchi. The course fee is only Rs. 1,50,000. The link is : - http://www.iimranchi.ac.in/ Regards, Deepak Rai

123

Kunal Jain
Kunal Jain

Hi Deepak, Thanks for the information. I wasn't sure whether the course would run this year at time of article writing and hence left it out. The course is worth considering at par with IIT Bombay and IIT Delhi. Kunal

123
Harun Murugavel
Harun Murugavel

Kunal , MICA also offers Post Graduate Certificate Programme in Market Research and Data Analytics through Ivory education for 1,00,000. http://www.mica.ac.in/home/learn-with-us/academic-programmes/post-graduate-certificate-programme-in-research-and-analytics

123

Kunal Jain
Kunal Jain

Thanks Harun for the information.

123
Swati
Swati

I have two years of experience in a reputed MNC in Software Testing. I am selected for the Certification in Business Analytics from ISB. I do not have any experience in Analytics just that I started working with the Digital Analytics team few months back in one of projects. Should I go for this course considering the huge investment that needs to be done? How's ROI ? Job prospects if I want to switch my company after this course?

123

Kunal Jain
Kunal Jain

Swati, The certification is one of the best programme available in India. Since it a recent programme, it is difficult to be sure on ROI. However, given the shortage of talent in industry, I would expect that you will have good job prospects after the course. Thanks, Kunal

123
Ankit gupta
Ankit gupta

Hi Swathi, Glad to hear that you are selected for ISB CBA, Even I am in a same state of confusion as whether to take up the offer(being so expensive). As Kunal rightly said we have no clue on the placements record of this course from ISB, since its a first batch. Please give me an update, if you have any track on this. Best, Ankit

123
Prashant
Prashant

Hi Swathi/Ankit Can you guys suggest what was the mode of selection? How was the test / interview? I'm willing to apply for Batch 2. Have 12+ ITeS exp. It would be a great help. Regards Prashant

123

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