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  • 2. Analytics Course Offerings Introduction to the training program Analytics foundation course o Probability Distributions, Data treatment, Correlation and variable studies, Statistical Modeling & Algorithms Tools foundation course o SAS, Excel, R, SPSS, SQL Domain Foundation course o Marketing, Retail, Online, Social Media and Call Center Analytics Advanced Analytics Course o Classification Techniques, Predictive Modeling, Forecasting and Optimization Techniques Custom Designed Courses o Specially designed courses based on organization/institute needs including workshops CONVERGYTICS CONFIDENTIAL 2
  • 3. Companies are increasingly turning to analytics to gain a competitiveadvantage. Most critical, however is the challenge posed by analyticaltalent, the people at all levels who help turn data into better decisions andbetter business results – Accenture on Analytical Talent, March 2010 Convergytics provides end to end analytical services, tools and solutions As can be seen from the above statement, business leaders across industries are realizing the importance of data based decision making because analytics has helped businesses in creating competitive edge, drive better strategies and save cost. However, there is a serious shortage of smart analytics professionals in the industry and while analytics requires some specialized skills, for most part people can develop skills through specialized training that uses industry examples to drive home the power of math. Convergytics identifies the need for quality analytics training programs that focuses on corporate/educational training needs and has collaborated with top management institutes like IIM-Bangalore, Indian Statistical Institute and alumni from London Business School to develop the training modules. The training focuses on providing in depth concepts around statistical modeling and also allows the user to understand the practical applicability by using case studies and hands on modeling/business solving exercises using actual industry examples. The training is built for all levels including beginner, intermediate and advanced users and the end of the training, the user will be adequately equipped to solve industry business problems. CONVERGYTICS CONFIDENTIAL 3
  • 4. Summary of the courses providedAnalytics Foundation Tools Foundation Advanced Analytics Domain Focused Training Training Training Training/WorkshopsWho should take this Who should take this Who should take this Who should take thistraining? training? training? training?Designed for beginners Designed for beginners Designed for analytics Designed for analyticsand intermediate level and intermediate level professionals with basic professionals with basicprofessionals and will professionals and will analytical skills and will analytical skills and willhelp build a base/ help enhance their enable users to apply help them acquireenhance understanding analytical usage with advanced techniques for domain specific analyticsin analytics analytical tools their problem solving skillsWhat does this course What does this course What does this course What does this coursedeliver? deliver? deliver? deliver?Basics of statistics, Solving examples of Predictive modeling, Workshops onvariable studies and different analytical Forecasting & Marketing, Finance,statistical modeling with problems using SAS, R, optimization techniques Retail, Social Media &real industry examples Excel, SPSS, Minitab with industry examples Call Center AnalyticsWhat is the duration of What is the duration of What is the duration of What is the duration ofthe program? the program? the program? the program?30 Hours 30 Hours 30 Hours 20 - 30 Hours CONVERGYTICS CONFIDENTIAL 4
  • 5. Analytics Foundation program Introduction to Analytics Data Cleaning & treatment - Outliers, Missing  What is Analytics?  Outlier Detection and Treatment  Case studies of application of analytics  Scatter Plots, Histograms, Percentiles  Analytics vs. data warehousing, OLAP  Tukey Test, Sigma Approach, MCMC method  Case Study – A large technology manufacturer Statistics  Variable Types & Dataset Measures Correlation  Data classifications  Linear correlation  Skewness, Kurtosis, Ranks & Univariate  Rank correlation  Case Study – A large technology manufacturer Probability Distributions  Discrete Probability Distributions Statistical Modeling o Binomial, Poisson  Introduction to statistical modeling  Continuous Probability Distributions  Classification Techniques o Normal, Chi-Square o CHAID  Probability Test of Hypothesis o K-Means, Rule Based o P value, Parametric test, F test, T test  Linear Regression  Non Parametric test  Logistic Regression o Chi square test, ANOVA  Case Study: A large technology manufacturer  Examples & Case Studies for each of the above modeling techniques CONVERGYTICS CONFIDENTIAL 5
  • 6. Tools Foundation program Using Excel for quick analysis Data creation  Overview of Excel  Creating variables in SAS  Sort, Filter o Variable Labels and Format  Formulas o Keep & Drop statements  Functions – Math, Text, Statistical & Date o SAS Functions - Math, String & Date  Conditional Functions – IF, IF THEN, o Conditional Processing  V Lookup/H Lookup  Data Manipulation  Pivot Table o Subsets, Append, Merge  Case Study: Create data sets for a large SAS technology manufacturer  Introduction of SAS o SAS Interface Common SAS Procedures and Options o Program Editor, Log, Output  Sort, Contents, Dataset, Means, Transpose, o DATA and PROC Plot, Summary, Options etc o PDV  Using Proc SQL  SAS Syntax o Rules for SAS Names Statistical Procedures and Functions o Rules for SAS Statements  Univariate, Freq, Regression, Correlation o Variable Types & Options  Case Study: A large technology manufacturer CONVERGYTICS CONFIDENTIAL 6
  • 7. Advanced analytics program Correlation Studies Classification  Linear Correlation  Basics & Assumptions of Classification  Rank Order Correlation  Linear Classification  Distance Correlation  Multinomial Logistic  Example & Case Studies  Decision trees  Case Study: Propensity to Buy for a large Clustering technology manufacturer  Introduction  Different type of segmentation Optimization  K-means algorithm  Basics of Optimization  ROCK Algorithm  Objective Function & Constraints  Case Study: Segmentation of customers for a  Linear Programming Problem large technology manufacturer  Case Study: Marketing budget optimization for A large technology manufacturer Regression  Basics of Regression Forecasting  Assumptions of GLM  Time Series Forecasting using basic  Building GLM models & Interpretation techniques like Auto Regression, Exponential  Violation of GLM assumptions  Advanced Techniques: ARCH, GARCH, ARIMAX  Case Study: Sales prediction for a large  Case Study: Demand forecasting for a large technology manufacturer technology manufacturer CONVERGYTICS CONFIDENTIAL 7
  • 8. Domain Focused Analytics Workshops Marketing Analytics workshop Social Media Analytics  Introduction to Marketing Analytics  Introduction to Social Media  Customer Profiling, Insights, RFM Analysis  Text Mining for Topic Modeling, Association  Customer Life Cycle Modeling rules & Sentiment analysis  Product Modeling & Market Basket Analysis  Segmentation of results by demographic &  Customer Lifetime Value other parameters for deeper insights  Media Mix Modeling  Qualitative Analysis & Tools: Radian 6  Integrated CRM Contact Strategy  Measurement Techniques Web Analytics workshop  Case Study: Creation of integrated contact  1 strategy for a large technology company  2  3 Retail Analytics  4  Financial Planning & Corporate Strategy  5  Store Operations Analytics  Assortment Planning & Optimization Finance Analytics  Pricing studies & Optimization  1  CRM & Marketing in Retail  2  Workforce planning & optimization  3  Supply Chain Analytics  4  5 CONVERGYTICS CONFIDENTIAL 8