An Overview of Analytics 180 or A180
DURATION
152 HOURS
PRICE
INR 25,000 /-
(PLUS 18% GST)
WHAT IT COVERS
R
PYTHON
ADVANCED PYTHON
BASE ANALYTICS
ADVANCED ANALYTICS (INCLUDES ARTIFICIAL INTELLIGENCE USING MACHINE LEARNING)
CLASS DAYS
WEEKDAYS:
TUE TO FRIDAY
WEEKENDS:
SATURDAY/SUNDAY
ADDITIONAL FEATURES
VALID FOR 365 DAYS FROM DATE OF REGISTRATION
COMPLIMENTARY ONLINE VIDEOS ON EXCEL, SQL, R, BASE ANALYTICS
COMPLIMENTARY GUEST LECTURES ON ANALYTICS
ELIGIBILITY TO APPLY TO RAP - INTERNSHIP PROGRAM IN ANALYTICS
Course Outline
R
DURATION: 16 HOURS
The R tool is an open source framework, which grew as a result of a strong push by Google. Today, R is poised to overtake SAS as the most widely used tool in statistical analyses. With over 20,000 packages currently available, it has near limitless potential for business application.
+ TOPIC 1: BASIC R PROGRAMMING
- R ENVIRONMENT AND WINDOWS SYSTEM
- R OBKECTS, DATA PERMANENCY AND REMOVING OBJECTS
- R HELP AND SEARCH WITH FUNCTIONS
- R COMMANDS AND CASE SENSITIVITY
- DATA IMPORT AND EXPORT
- PACKAGES
- R INSTALLATION
- SIMPLE MANIPULATIONS: NUMBERS AND VECTORS
- WRITING YOUR OWN FUNCTIONS
+ TOPIC 2: ADVANCED APPLICATIONS OF R
- DATA MANIPULATION: MERGING, SORTING, FILTERING, DE-DUPING
- USER DEFINED FUNCTIONS
- VISUALIZATIONS: HISTOGRAM, BAR PLOT, BOX PLOT, MOSAICS PLOT, GEOGRAPHICS PLOT
BASE ANALYTICS
DURATION: 48 HOURS
Analytics Base (AB) includes fundamental concepts of statistics, and guides in building predictive models using multiple linear and logistic regressions. All of this is taught using live case studies with data from 18 different industries, at ATI.
+ TOPIC 1: INTRODUCTION TO ANALYTICS
- OVERVIEW
- NEED FOR ANALYTICS
- USE OF ANALYTICS ACROSS DIFFERENT INDUSTRIES
- CHALLENGES IN ADOPTION OF ANALYTICS
+ TOPIC 2: DESCRIPTIVE ANALYTICS
- OVERVIEW
- UNDERSTANDING DIFFERENT OUTPUTS
- TABULAR AND GRAPHICAL METHOD
- SUMMARY STATISTICS
+ TOPIC 3: STATISTICAL TESTING
- HYPOTHESIS TESTING
- Z TEST, T TEST, CHI SQUARE TEST, ANOVA
- PARAMETRIC AND NON PARAMETRIC TEST
+ TOPIC 4: REGRESSION AND CORRELATION
- OVERVIEW
- HOW TO CARRY OUT REGRESSION
- TYPES OF REGRESSION - LOGISTIC AND LINEAR
- CASE STUDIES
+ TOPIC 5: MODELING TECHNIQUES
- OVERVIEW
- CONCEPTS OF SEGMENTATION
- USE OF SEGMENTATION
- CLUSTER ANALYSIS FACTOR ANALYSIS
ADVANCED ANALYTICS
DURATION: 48 HOURS
With the aid of live projects, Advanced Analytics teaches you how to:
-Make your data look good using data visualization
-Forecast using time series
-Find patterns in large amount of text using text analytics
- Machine Learning
+ TOPIC 1: TEXT ANALYTICS
- PROBLEMS WITH UNSTRUCTURED DATA
- TERMINOLOGY IN TEXT ANALYTICS: CORPUS, TDM, PARSING, STEMMING,STOPWORDS, CHUNKING ETC
- CLASSIFICATION AND TAGGING
- IN CLASS PROJECT: DOCUMENT CLASSIFIER AND SENTIMENT ANALYSIS
+ TOPIC 2: AUTOMATION IN TIME SERIES
- TIME SERIES DECOMPOSITION
- COMMON TECHNIQUES LIKE MOVING AVERAGES, SMOOTHING ETC
- ARIMA
- IN CLASS PROJECT TO AUTOMATE FORECASTING
+ TOPIC 3: MACHINE LEARNING
- WHAT IS MACHINE LEARNING
- TREE BASED LEARNING
- COMMON LEARNERS: KNN, RANDOM FORESTS, GBM ETC
- IN CLASS PROJECT
+ TOPIC 4: DATA VISUALIZATION
- LANDSCAPE OF VISUALIZATION
- THINKING VISUALLY
- HOW TO CHOOSE APPROPRIATE VISUALS
- STORYBOARDING
- IN CLASS PROJECT
