Trainings

Data Science & Insights Trainings

Classroom:Machine Learning using R

Learn R with DnI Institute Machine learning techniques are increasingly adopted to iterative learning from data for finding patterns, insights and improving accuracy of the advanced analytics models. Some of the industry voices on why machine learning is important  
  • • “A breakthrough in machine learning would be worth ten Microsofts” (Bill Gates, Chairman, Microsoft)
  • • “Machine learning is the next Internet” (Tony Tether, Director, DARPA)
  • • “Machine learning is going to result in a real revolution” (Greg Papadopoulos, Former CTO, Sun)
  • • “Machine learning is today’s discontinuity” (Jerry Yang, Founder, Yahoo)
  • • “Machine learning today is one of the hottest aspects of computer science” (Steve Ballmer, CEO, Microsoft

Machine Learning Algorithms experience could help you in advancing your analytics/data science career.  Also, you may use the learning in bringing innovative products or solutions.

Training Logistics and Information

Contact us @ info@dni-institute.in  or Visit www.dni-institute.in for more details
  • Contact us for a demo class
  • Classroom: BTM Bangalore and Online Instructor Based
  • Training Hours: 40 Hours
  • Weekend Batch of max capacity 6 folks (Hurry up contact us and enrol for the training)

 

Training Contents

 

Who Should Attend?

Classification and Regression problems have been solved by age old statistical techniques, many new Statistical & Machine Learning Algorithms are applied to improve modeling accuracy and solve new business problems. The training program covers theoretical concepts of machine learning algorithms and application details with case studies.

Training Contents
  • • Modeling Framework Overview
  • • Foundational Steps: Business Context, target Variable Definition, Data Preparation (e.g. reading, aggregation, missing value & outlier treatment etc )
  • • Support Vector Machine (SVM) - Concepts & Terminology
  • • SVM using R- A Case Study
  • • Random Forest - Concepts & Terminology
  • • Random Forest using R- A Case Study
  • • Gradient Boosting (GBM) - Concepts & Terminology
  • • GBM using R- A Case Study
  • • Assignment Project for candidates
  • • Increasingly, a number of real life analytics problems are solved by machine learning algorithm, but very few people have high level understanding & applications experience. Candidates who wants to build Machine Learning expertise & experience could join the journey with us.
  • • Candidates who have BI & Reporting experience and are looking to get into Credit Risk Analytics for Banks or Financial Services.
  • • Individuals who have decent level of Statistical/Analytics experience and are looking to develop experience of Data Science & Machine Learning Techniques
  • • Course will be conducted using SAS Or R/R Studio, so candidates are expected to have programming knowledge (Training for building Learn SAS programming skills and R programming skills).
  • • Candidates who have risk functional knowledge and wants to build credit risk analytics experience.
  • • It is assumed that the candidates have decent level of analytics experience, though risk analytics course will be started from basics and in a systematic way.

 

Why DnI Institute?

  • • Personalized Analytics training with max batch size of 8 candidates
  • • Learn Analytics from Industry stalwarts with deep Analytics & domain experience
  • • Trainers have extensive corporate and teaching experience – worked with companies like Genpact, Infosys, Accenture, HSBC and conducted analytics courses at MICA, GIM, Great lakes, IITs and IIMs
  • • Course will be a blend of Industry use cases and practical scenarios/case studies/examples
  • • Guest lecture(s) from Industry experts
  • • Selected candidates considered for Internship @ DnI Institute

Contact us if you want the training Online


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