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The Analytics 360 Course

A comprehensive course for beginners: 5 modules comprising of Excel, Python, Power BI, SQL, and Base Analytics. Read more about the course structure below.

Course Outline

ADVANCED EXCEL

DURATION: 24 HOURS

Excel is by far the world's most popular spreadsheet, used pretty much everywhere you look in the business world, especially in areas where people are adding up numbers a lot, like marketing, business development, sales, finance, etc. Thus, Excel in its universality is now a must have skill in every business environment.

TOPIC 1: INTRODUCTION TO EXCEL


  • OVERVIEW
  • HOME TAB
  • CONDITIONAL FORMAT
  • PASTE SPECIAL
  • GO TO SPECIAL




TOPIC 2: DATA TAB


  • OVERVIEW
  • SIMPLE SORT AND FILTER
  • ADVANCED SORT AND FILTER
  • WHAT IF ANALYSIS
  • DATA VALIDATION




TOPIC 3: FUNCTIONS


  • TEXT FUNCTIONS LIKE CONCATENATE, TRIM, SEARCH AND SUBSTITUTE
  • LOGICAL FUNCTIONS LIKE IF, AND, OR
  • LOOKUP FUNCTIONS LIKE VLOOKUP, HLOOKUP, REFERENCE, INDEX AND MATCH
  • ADVANCED FUNCTIONS LIKE DCOUNT, DSUM




TOPIC 4: DYNAMIC CHARTS AND PIVOT TABLES


  • OVERVIEW
  • CREATING CHARTS AND USING DYNAMIC CHARTS
  • CONNECTING TO FORM CONTROLS
  • SIMPLE PIVOT TABLES AND FUNCTIONS IN PIVOT TABLES
  • INTEGRATING CHARTS WITH TABLES




TOPIC 5: VBA/MACROS


  • WRITING SUB ROUTINES
  • LOOPS
  • CONDITIONAL STATEMENTS
  • PRIVATE SUB ROUTINES
  • UDFS




TOPIC 6: USERFORMS


  • CREATING USERFORMS
  • USING SIMPLE VALIDATIONS





SQL

DURATION: 24 HOURS

Structured Query language (SQL) is a computer language used to access a database. It is used for updating data on a database.

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





POWER BI

DURATION: 16 HOURS

Power BI is a business analytics service by Microsoft. It aims to provide interactive visualisations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

TOPIC 1: INTRODUCTION TO POWER BI


  • INSTALLING POWER BI DESKTOP
  • EXPLORING VARIOUS DATA SOURCES
  • CONNECT TO DATA IN POWER BI DESKTOP




TOPIC 2: QUERY EDITOR IN POWER BI


  • RENAMING QUERIES
  • COMBINING QUERIES: APPEND
  • FIXING METADATA
  • FILTERING ROWS
  • ELIMINATING COLUMNS
  • COMBINING QUERIES: MERGE
  • ADDING A COLUMN




TOPIC 3: TRANSFORMING DATA


  • DIRECT QUERY VS IMPORT DATA
  • SHAPE & COMBINE
  • DATA TYPES
  • GROUPS JOINS AND BINS
  • SPLIT COLUMN




TOPIC 4: FILTERS & SLICERS


  • BASIC FILTERS & ADVANCED FILTERS
  • PAGE AND REPORT FILTERS
  • DRILL THROUGH FILTERS




TOPIC 5: CHARTS & CONCEPTS


  • VARIOUS CHARTS
  • MATRIX, TABLE MAP, R VISUALS




TOPIC 6: CREATING REPORTS


  • CREATING REPORTS
  • RENAMING A DATASET AND REPORT
  • GET INSIGHTS




TOPIC 7: DAX FUNCTIONS


  • STRING MATH AND LOGICAL
  • AGGREGATE
  • DATE AND TIME INTELLIGENCE




TOPIC 8: CREATING DATASETS


  • CREATE AND MANAGE RELATIONSHIPS
  • CALCULATED FIELDS
  • COLUMNS (CALCULATED AND CONDITIONAL)
  • MEASURES HIERARCHIES AND TABLES
  • PERFORMING A LOOKUP TO A RELATED TABLES
  • TRANSLATING A VALUE
  • ENHANCING THE DATA MODEL




TOPIC 9: SHARING & EXPLORING POWER BI DASHBOARDS


  • ADDING TITLE
  • ACTIONS AND REPORTS
  • POWER BI Q&A





BASE ANALYTICS

DURATION: 40 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





PYTHON

DURATION: 24 HOURS

Python is an open source scripting language, known for its simplicity.


It is extremely powerful and can be used for almost any statistical or analytical operation. As it is widely used in web development, it acts as an ideal bridge to support analytics in web based applications.

TOPIC 1: INTRODUCTION TO POWER BI


  • INSTALLING POWER BI DESKTOP
  • EXPLORING VARIOUS DATA SOURCES
  • CONNECT TO DATA IN POWER BI DESKTOP




TOPIC 2: QUERY EDITOR IN POWER BI


  • RENAMING QUERIES
  • COMBINING QUERIES: APPEND
  • FIXING METADATA
  • FILTERING ROWS
  • ELIMINATING COLUMNS
  • COMBINING QUERIES: MERGE
  • ADDING A COLUMN




TOPIC 3: TRANSFORMING DATA


  • DIRECT QUERY VS IMPORT DATA
  • SHAPE & COMBINE
  • DATA TYPES
  • GROUPS JOINS AND BINS
  • SPLIT COLUMN




TOPIC 4: FILTERS & SLICERS


  • BASIC FILTERS & ADVANCED FILTERS
  • PAGE AND REPORT FILTERS
  • DRILL THROUGH FILTERS




TOPIC 5: CHARTS & CONCEPTS


  • VARIOUS CHARTS
  • MATRIX, TABLE MAP, R VISUALS




TOPIC 6: CREATING REPORTS


  • CREATING REPORTS
  • RENAMING A DATASET AND REPORT
  • GET INSIGHTS




TOPIC 7: DAX FUNCTIONS


  • STRING MATH AND LOGICAL
  • AGGREGATE
  • DATE AND TIME INTELLIGENCE




TOPIC 8: CREATING DATASETS


  • CREATE AND MANAGE RELATIONSHIPS
  • CALCULATED FIELDS
  • COLUMNS (CALCULATED AND CONDITIONAL)
  • MEASURES HIERARCHIES AND TABLES
  • PERFORMING A LOOKUP TO A RELATED TABLES
  • TRANSLATING A VALUE
  • ENHANCING THE DATA MODEL




TOPIC 9: SHARING & EXPLORING POWER BI DASHBOARDS


  • ADDING TITLE
  • ACTIONS AND REPORTS
  • POWER BI Q&A





ADVANCED ANALYTICS

DURATION: 40 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