Diversify Data Science & Insights Knowledge

Diversify Data Science & Insights Knowledge

DnI Training programs are designed to help your learning about different applications of Data Science & Insights across business problems, changing functional area or Industry vertical, learning additional Statistical & its applications.

The trainings are designed to build your experience in a relevant business vertical, functional area and Tools & Techniques.

Some of the example scenarios why you may be interested in DnI offered trainings

Scope Scenarios

Business Vertical

have spent a few years on applying Data Science & Insights for a vertical (e.g. financial Services) and want to explore Data Science & Insights applications in other business vertical e.g. retail & CPG or Healthcare

Have heard about certain applications of analytics, for example Market Basket Analysis (MBA) applications in Retail & CPG scenario and is interested to understand the theory, methodology and step by step working with an example

Wanted to build industry knowledge of a vertical and looking for structured support to build the knowledge and be confident of my understanding Have been looking to change my job and acquiring knowledge of different business vertical could help me in getting the job and also do better in the new job

Functional Areas

Have acquired good understanding of customer analytics and looking forward to diversify experience in Fraud or Retail Analytics

You believe that scope of Data Science & Insights application in a particular functional area is high but you do not have the required knowledge & experience; hence looking for trainings to acquire the required skills and expertise.

Each functional area has a few nuances and want to experience of those nuances with working examples

Techniques and Application Based

Have been working on various ad-hoc & strategic analytics projects and interested to develop understanding of statistical & machine learning techniques

Have used logistic regression for developing predictive models and now want to explore how Neural Network, Decision Tree, Support Vector Machine (SVM) and other techniques are applied

Have used some of the statistical techniques but not sure if those were best ways to do and want to get wider perspective

Curious to understand applications of data science & insights using social media and un-structured data

Complicated Applications of Data Sciences

Next Best Action (NBA):

What is Next Best Action (NBA) framework? How Next Best Action (NBA) is applied in various business scenarios?

Customer Life Time Value (CLTV):

How Customer Life Time Value (CLTV) is applied for business scenarios? What are the building blocks of CLTV?

Survival Modeling for attrition:

How can survival model be applied for customer attrition and/or balance erosion?

Some of the Data Science & Insights trainings available are