Analytics for All: Beginners to Experts
About This Course
Course Description
Analytics is a huge and steadily growing industry. There is so much that can be done with the enormous amount of data available to us. The big data and analytics market will reach $125 billion worldwide in 2015, according to IDC. Ready to get on the bandwagon?
How do I increase my page’s Facebook likes? How do I know if blue or green would be good for my company’s logo? Which of the 10 methods would be most cost effective? Let analytics answer your questions and help you make databacked, strategic and quicker decisions.
Whether you’re new to the field and want to tip toe into analytics or you’ve taken the big dive and are ready to immerse yourself in the subject, this course is for you!
Acquire a deep understanding of analytics and the tools and techniques involved.
Our content is periodically updated to make sure we give you the best. Our course material is designed in a way to ensure that you’re gripped right from the basics. Become an expert in 8 weeks! We don’t just give you 143 lectures and 23+ hours of content,we provide you lifetime access to all the material to accommodate your busy work schedule.
Additionally, you can get all your questions answered on our discussion forum and find examples and solutions uploaded by us and other students. Stay connected with your professors and peers 24*7!
Analytics propels clarity and innovative thinking. At ATI, we are committed to get your mind churning the right way.
What’s in it for you?
·Automate work using Excel
·Learn to create dashboards and make your data visually appealing
·Hypothesis testing: Make no assumptions
·Ace Linear and Logistic Regression
·Use Cluster and Factor analysis to find associations
·Master R and SAS.
·SQL Basics
·15 case studies and regular quizzes to gauge your understanding.
What after the course?
·Enter a Kaggle competition, get recognized and win $100,000 or more?
·Start your own company? Artificial intelligence maybe?
·Get your company acquired by the big players?
·Write for the Wall Street Journal?
There is so much you can do with analytics – from predicting who will win a political election to foreseeing the occurrence of an earthquake; it is a world of uncertainty that can be made certain.
Enroll now!
And oh, it doesn’t end here,
Use our Facebook page to interact with thousands of other students and professionals. Keep up with the market and network with like minds.
What are the requirements?
 High school mathematics skills
 Software: MS Excel, R and SAS must be installed in your system before you take up the course
 Need to make a time frame for yourself to complete the course. As you learn at your own pace and convenience, you have to make your own deadlines and keep it
 Start exciting discussions
 Skype your queries to udemy.support between 8.30AM to 5.30PM – IST or mail us – help@analyticstraining.in.We will respond to your queries within 24 Hrs
What am I going to get from this course?
 By the end of this course Data won’t be overwhelming anymore and you will be making great insights like a pro
 Application! You will be be able to apply what you learn in multiple areas like HR, marketing, finance, sales, sports etc
 You will be able to use advanced tools like R and SAS which are industry requirements in analytics
 You will be able to build Predictive Models to like Logistic and Linear regression
 You will be able to relate any concept with real life examples
 You will get to interact with students and connect with instructors in our regular live sessions. If you have your own dataset you can use these sessions to help you skillfully maneuver your own data.
What is the target audience?
 If your job throws out more data than you can handle today, this course is for you.
 If your career is slowing down, and need a shift, analytics could be for you.
 If you are keen on getting into the analytics industry as a fresher.
 For people who don’t have a strong knowledge of statistics, but feel it would help their job productivity.
 Absolute beginners with no prior knowledge of Analytics
 And those who have some prior knowledge.
Curriculum
Section 1: Agenda  

Lecture 1 
Why Analytics and What you will learn

01:18  
Lecture 2 
How to go about learning

02:17  
Lecture 3 
Fast Track Guide

6 pages  
Lecture 4 
A peek into the future

04:20  
Section 2: The analytics learning kit  
Lecture 5 
One Stop for all study material

5 pages  
Lecture 6 
SAS Installation Guide (University Edition)

3 pages  
Lecture 7 
RInstallation Guide

2 pages  
Lecture 8 
Case Studies

Article  
Section 3: Simple speak: What is analytics?  
Lecture 9 
What is analytics?

00:42  
Lecture 10 
Patterns around us

09:43  
Lecture 11 
How it works

09:33  
Lecture 12 
Applications in the industry

09:35  
Section 4: MS Excel: Offload your work  
Lecture 13 
Why you need to know Excel

00:38  
Lecture 14 
What you will Learn

01:03  
Lecture 15 
Get to know Excel in 20 minutes

20:53  
Quiz 1 
Are you ready to offload your work?

5 questions  
Section 5: Data Cleaning  
Lecture 16 
Why you need to know about Data cleaning

01:03  
Lecture 17 
How you can clean Data

00:33  
Lecture 18 
Customize a List – NEW VIDEO

05:47  
Lecture 19 
Format numbers

06:03  
Lecture 20 
Coloring cells the smarter way

09:44  
Lecture 21 
Going beyond a simple Paste

06:22  
Lecture 22 
Going beyond a simple Find

05:14  
Lecture 23 
Text to Columns – An easy but important concept – See why!

07:59  
Quiz 2 
How well have you understood Data Cleaning

4 questions  
Lecture 24 
Case Study

3 pages  
Section 6: Organizing data in Excel  
Lecture 25 
Organizing data in excel

00:38  
Lecture 26 
How to organize data in Excel

00:51  
Lecture 27 
Using Shortcuts

05:05  
Lecture 28 
Is your data readable?

12:08  
Lecture 29 
Deciding what others enter

06:23  
Lecture 30 
Creating totals per segment

05:07  
Lecture 31 
Consolidating Tables

09:30  
Quiz 3 
How well have you understood Organizing Data

5 questions  
Section 7: Using Excel as a decision tool  
Lecture 32 
Using Excel as a decision tool

00:49  
Lecture 33 
Goal Seek – NEW VIDEO

05:38  
Lecture 34 
SOLVER: Let Excel make a smarter choice for you

09:45  
Lecture 35 
Data Table: Decision Table

09:55  
Lecture 36 
What If Analysis: Let Excel create a decision table for you

05:19  
Section 8: writing smart Functions in Excel  
Lecture 37 
Writing smart functions in Excel

00:47  
Lecture 38 
How Functions can help

00:37  
Lecture 39 
Learn tricks to self explore Excel Functions

10:28  
Lecture 40 
What a function needs to deliver the required output

04:55  
Lecture 41 
Difference B/W Summary and a Self Learning Template

03:43  
Lecture 42 
Convert a Count summary to a template

10:01  
Lecture 43 
How to choose what to Count

15:48  
Lecture 44 
Using Text Functions for Data Cleaning

12:53  
Section 9: Segmenting Data in Excel  
Lecture 45 
Segmenting data in Excel preview

00:42  
Lecture 46 
How to segment your Data

00:27  
Lecture 47 
Dividing data into meaningful segments

08:55  
Lecture 48 
Dividing data using multiple conditions

07:01  
Section 10: Why create reports the tedious way  
Lecture 49 
Why create reports the tedious way?

00:43  
Lecture 50 
How Pivots make data meaningful

10 pages  
Lecture 51 
Introduction to Pivots

06:32  
Lecture 52 
Creating reports without getting into technicalties

07:29  
Lecture 53 
Slicing reports with Pivots

02:30  
Lecture 54 
Working with dates in Pivots

06:30  
Section 11: Showcasing your data with Excel  
Lecture 55 
Excel dashboards: Preview for the section Showcasing your data with Excel

01:09  
Lecture 56 
Using Dashboards to make data look good

13 pages  
Lecture 57 
How to create a Dashboard

00:35  
Lecture 58 
Different ways to present Data

06:25  
Lecture 59 
Creating a Dashboard Template

10:12  
Lecture 60 
Making Templates smarter

10:36  
Lecture 61 
Converting Templates to a Dashboard by Adding controls

10:20  
Lecture 62 
Dashboard on multiple source of Data

10:43  
Section 12: Case Study  
Lecture 63 
Excel Case study preview

00:52  
Lecture 64 
Revenue Report

6 pages  
Section 13: Advanced Excel (VBA & MACROS) – The A, B, Cs  
Lecture 65 
Introduction to VBA Programming

03:52  
Lecture 66 
OOPS

04:15  
Lecture 67 
Hierarchy as a vocabulary of the language

02:59  
Lecture 68 
Communication among objects

03:24  
Lecture 69 
Examples to justify the communication techniques

03:33  
Lecture 70 
Introducing Intangible Hierarchy

04:11  
Section 14: Grammar  
Lecture 71 
Sentence creation : Connections in Excel

02:09  
Lecture 72 
Rules of writing sentences in VBA

04:30  
Section 15: Learn more with handson : Introducing the platform to write and automate  
Lecture 73 
Introducing the platform : VBA window

05:48  
Section 16: Small exercises to connect our learning so far  
Lecture 74 
Applying Functions in VBA

11:12  
Lecture 75 
Applying properties in VBA

09:24  
Lecture 76 
Applying methods in VBA

04:13  
Lecture 77 
Various ways of executing a Macro

09:36  
Section 17: Implementation on a case study  
Lecture 78 
Explaining case study for hands on learning

02:10  
Lecture 79 
Understanding the IF statements

11:23  
Lecture 80 
Converting constants to variables

04:19  
Lecture 81 
Understanding Loops : For Next

05:49  
Lecture 82 
Understanding Loops : Do Loops

10:24  
Lecture 83 
Recording a Macro : Hand Holding/Onjob training to Macros

07:22  
Lecture 84 
Trailing Macros – one after another

06:36  
Section 18: Functions and Events can also be customised  
Lecture 85 
Events to self execute your Macros

10:19  
Lecture 86 
Creating your own functions in Excel

10:20  
Section 19: Analytics  
Lecture 87 
Tour of data mining techniques

03:54  
Quiz 4 
Pretest: Find out how much you don’t know

4 questions  
Section 20: Hypothesis Testing: How to prove something wrong  
Lecture 88 
Hypothesis testing

00:41  
Lecture 89 
Telecom churn: Case under study

01:26  
Lecture 90 
The basics: High school math you’ve probably forgotten

02:56  
Lecture 91 
Means and medians

06:20  
Lecture 92 
Probability: The reason you haven’t won the lottery

06:07  
Lecture 93 
Confidence intervals: How to know what you don’t know

05:44  
Lecture 94 
TStat: Your first new statistic

06:33  
Lecture 95 
Example

06:35  
Lecture 96 
1 sample ttest: Checking means

04:30  
Lecture 97 
2 sample ttest: Does TV make you buy things

04:22  
Lecture 98 
ANOVA: Your car brand and your dinner bill

03:10  
Lecture 99 
Chisquare TOI: One category on an another

03:06  
Lecture 100 
Cheat sheet: So you don’t have to remember all of it

02:49  
Lecture 101 
Questions you might have

Article  
Quiz 5 
Understood it all?

3 questions  
Quiz 6 
Check your Understanding

5 questions  
Section 21: Linear regression: Lines and dots  
Lecture 102 
Regression Preview

00:48  
Lecture 103 
How much should your house cost?

11:26  
Lecture 104 
Building your model using R

01:00  
Lecture 105 
Step 1: Import your data

02:49  
Lecture 106 
Step 2: Use the lm function to build a model

02:02  
Lecture 107 
Step 3: Split your dataset

01:29  
Lecture 108 
Step 4: Model selection

02:49  
Lecture 109 
Step 5: Multicollinearity

02:09  
Lecture 110 
Step 6: Predict and check quality

03:32  
Quiz 7 
Check your Understanding

5 questions  
Section 22: Logistic Regression  
Lecture 111 
How to spot dissatisfied customers

04:50  
Lecture 112 
The math behind it

03:00  
Lecture 113 
Building a logistic regression using R

01:10  
Lecture 114 
Step 1: Importing and summarizing data

02:14  
Lecture 115 
Step 2: Learn how to use the “glm” function

03:15  
Lecture 116 
Step 3: Prepare your data

01:36  
Lecture 117 
Step 4: Select the appropriate model

03:16  
Lecture 118 
Step 5: Finally make your predictions

04:39  
Lecture 119 
Step 6: Check your model performance

06:22  
Quiz 8 
Check your understanding

5 questions  
Section 23: Titanic Case Study – Logistic Regression  
Lecture 120 
Titanic data

2 pages  
Lecture 121 
The ANSWER

19:19  
Section 24: Cluster analysis  
Lecture 122 
Cluster & Factor Analysis Preview

01:17  
Lecture 123 
Segmenting data – The KMeans algorithm

00:51  
Lecture 124 
Step 1: Import your data

01:37  
Lecture 125 
Step 2: Specify number of clusters

03:15  
Lecture 126 
Step 3: Interpret your cluster output

04:48  
Quiz 9 
Check your understanding

5 questions  
Section 25: Factor analysis: Behind the scenes  
Lecture 127 
Where do we use factor analysis

01:11  
Lecture 128 
FACTANAL README

Article  
Lecture 129 
Framework for Factors : Using R tool

02:59  
Lecture 130 
Computing factor loadings

05:09  
Lecture 131 
Scoring survey

01:27  
Quiz 10 
Check your Understanding

5 questions  
Section 26: Tips and tricks on Analytics – Do more than you thought you could !  
Lecture 132 
3 cool tricks on Regression – These will give you an edge over the others !

11:19  
Section 27: Case studies: Real life data to test your brand new skills  
Lecture 133 
World Bank Loan data

4 pages  
Lecture 134 
Understanding how we learn at school

1 page  
Lecture 135 
Pro level: Medicare data case study

1 page  
Lecture 136 
Mortality Data: Identify the Causes

1 page  
Lecture 137 
Medicare Data: Get to the roots

1 page  
Lecture 138 
How critical can malaria be

1 page  
Lecture 139 
Dialysis Data: What, How, Who and When

1 page  
Section 28: R Getting Started  
Lecture 140 
The RHandbook : For the Frequent travelers

133 pages  
Lecture 141 
R getting started

00:56  
Lecture 142 
What and Why of R

03:54  
Lecture 143 
Know your Tool : Installing R and R Studio

05:02  
Lecture 144 
Introducing the Data Types

07:33  
Lecture 145 
Introducing the Data Structures : Learn How to create Vectors

19:48  
Lecture 146 
Data Structure : Data Frame in R

11:16  
Lecture 147 
Data Structure : List and Matrix in R

08:06  
Lecture 148 
Factors : Last Data Type

02:55  
Quiz 11 
Check your understanding

5 questions  
Section 29: Advance Operations in R  
Lecture 149 
Data Handling Part 1 : Introduction to Package and reading files

13:58  
Lecture 150 
Data Handling Part 2 : Write files in R

06:02  
Lecture 151 
Logical Operations and If Conditional

11:55  
Lecture 152 
Learn How to Merge your tables

08:45  
Lecture 153 
Text Analytics : Terms and Terminologies

15:40  
Lecture 154 
Text Analytics Project Part 1 : Creating word cloud on Tweet Archive

27:15  
Quiz 12 
Check your understanding

5 questions  
Section 30: R Section Task and Codes  
Lecture 155 
Lecture Presentation

36 pages  
Lecture 156 
Practice Excercise : Try and Test what you have learned so far

1 page  
Section 31: Getting Started: SAS  
Lecture 157 
How to start talking SAS

11:47  
Lecture 158 
Your first SAS code

12:28  
Lecture 159 
Importing External files

11:10  
Quiz 13 
Check your understanding

5 questions  
Section 32: Data Understanding  
Lecture 160 
Understanding data structure

03:34  
Lecture 161 
Viewing the data

07:26  
Lecture 162 
Sorting data

06:33  
Lecture 163 
Copying data sets

03:43  
Lecture 164 
Creating Sample datasets

02:05  
Lecture 165 
Selecting Variables

04:13  
Quiz 14 
Check your Understanding

5 questions  
Section 33: Applying Conditions  
Lecture 166 
Conditional Statement – ‘Where’

06:08  
Lecture 167 
Conditional statement – ‘IF’

12:36  
Section 34: Combining datasets  
Lecture 168 
Appending datasets

09:08  
Quiz 15 
Check your understanding

5 questions  
Lecture 169 
Merging datasets

16:55  
Quiz 16 
Check your understanding

5 questions  
Section 35: How to count in SAS  
Lecture 170 
Proc Freq: Where are your customers coming from?

00:49  
Lecture 171 
How to select the variables you want to analyze.

01:13  
Quiz 17 
Proc Freq

6 questions  
Lecture 172 
Cross Tab: Which brand sells in which city

02:51  
Lecture 173 
How do you save your output

01:24  
Quiz 18 
Proc Freq – Cross tab

7 questions  
Section 36: Getting SAS to do the math: Mean, Median, etc.  
Lecture 174 
Proc Means: What are your average expenses

01:39  
Quiz 19 
Proc Means

5 questions  
Lecture 175 
How do you find the average for each segment

02:01  
Quiz 20 
Proc Means – Grouping

5 questions  
Lecture 176 
What other statistics can you calculate?

01:02  
Lecture 177 
How to save your output

05:22  
Quiz 21 
Proc Means – select statistics & store output

5 questions  
Lecture 178 
Proc Summary: An alternative

01:31  
Quiz 22 
Proc summary

5 questions  
Section 37: Save your results in different file formats  
Lecture 179 
Storing output in HTML file

02:30  
Lecture 180 
Storing output in other file formats

02:59  
Quiz 23 
Check your Understanding

5 questions  
Section 38: How to Export your data in different file formats  
Lecture 181 
Exporting data to a CSV file.

01:29  
Lecture 182 
Exporting data to a TXT file

01:18  
Lecture 183 
Exporting data to a TXT file with delimiter.

00:37  
Quiz 24 
ODS & Exporting

8 questions  
Section 39: Functions: Getting SAS to do the heavy lifting  
Lecture 184 
Dealing with numbers

02:43  
Quiz 25 
Numeric Functions

4 questions  
Lecture 185 
Dealing with Text

03:04  
Lecture 186 
Text functions continued…

05:15  
Lecture 187 
Find Function: Searching inside text

04:39  
Quiz 26 
Character Functions

5 questions  
Lecture 188 
Dealing with dates

08:57  
Quiz 27 
Date Functions

9 questions  
Lecture 189 
Dealing with decimals

02:01  
Quiz 28 
Restrict decimal values

2 questions  
Section 40: Loops: Why redo?  
Lecture 190 
Do Loop: The simplest way to loop

10:52  
Lecture 191 
Smarter looping

05:04  
Quiz 29 
Loops

7 questions  
Lecture 192 
Arrays: Working with multiple variables at the same time

07:46  
Quiz 30 
Arrays

7 questions  
Section 41: How to Make good Looking reports?  
Lecture 193 
Proc Report: Summarizing all your findings

09:49  
Quiz 31 
Proc Report

4 questions  
Section 42: Automating your projects  
Lecture 194 
How to create a macro?

08:56  
Lecture 195 
Parameters: Passing values into a macro

06:24  
Lecture 196 
Reusing your macros

13:18  
Quiz 32 
Macros

6 questions  
Section 43: How to write SQL queries in SAS?  
Lecture 197 
SQL Basics

06:26  
Quiz 33 
SQL Basics

5 questions  
Lecture 198 
Getting SQL to calculate the statistics

09:11  
Lecture 199 
Writing nested queries

05:17  
Quiz 34 
SQL data preparation

4 questions  
Section 44: Understand what the data wants to tell you  
Lecture 200 
SQL Indexes

06:27  
Quiz 35 
Check your Understanding

5 questions  
Section 45: Case Studies  
Lecture 201 
Back to school

11:03  
Lecture 202 
Don’t let your customers say bye to you

12:21  
Lecture 203 
How old was the last abalone you had?

14:54  
Lecture 204 
How good are you with choosing the right flower?

12:27  
Section 46: Fun with Data Test your skills  
Lecture 205 
Want to start a company? Know your market

1 page  
Lecture 206 
Would you buy an insurance policy for a caravan?

4 pages  
Lecture 207 
Blood Brain Model

1 page  
Lecture 208 
Churn Rate of Telecom Customer Base

2 pages  
Lecture 209 
Credit Banking

1 page  
Lecture 210 
How is the Business going Good, bad, Ugly?

1 page  
Lecture 211 
Campaign Testing

1 page  
Lecture 212 
Find the Credit Score

1 page  
Lecture 213 
Sales Data – Computer Peropherals

1 page  
Lecture 214 
Customer Segmentation – a retail case study

1 page  
Lecture 215 
Market Basket Analysis

1 page  
Lecture 216 
Global Health World Data

1 page  
Lecture 217 
Factors other than food intake that controls your weight

1 page  
Lecture 218 
Clinical Trial

2 pages  
Lecture 219 
Data on Dialysis Centers

1 page  
Section 47: Make Sense of Data  
Lecture 220 
What you’ve got to do

1 page  
Lecture 221 
Advertising Expenditure by Medium (19502006)

Article  
Lecture 222 
Agricultural exports and imports

Article  
Lecture 223 
Grandparents living with grandchildren ( by race and sex)

Article  
Lecture 224 
Average hours worked by Employed persons

Article  
Lecture 225 
People with jobs but not at work

Article  
Lecture 226 
Dataset on multilingual Children (English and other language)

Article  
Lecture 227 
Fruits and Vegetables (supply and use)

Article  
Lecture 228 
Crime Rates by State (US)

Article  
Lecture 229 
International Travel by US residents

Article  
Lecture 230 
Percentage of Adults engaging in Leisure Time

Article  
Section 48: DATA CHALLENGE 1 – Work That Data  
Lecture 231 
The RULES

3 pages  
Lecture 232 
Data Set 1: Meteorite Data

1 page  
Lecture 233 
Data Set 2: Groundwater Depletion Rates

Article  
Lecture 234 
Data Set 3 : Exam Data

Article  
Section 49: Case Study  
Lecture 235 
This is for the retailers You can never go wrong with this

3 pages  
Lecture 236 
This could be the reason you never gain weight!

3 pages  
Lecture 237 
Snails – Yes, those slimy little creatures

4 pages  
Lecture 238 
Are you being targeted?

4 pages  
Lecture 239 
Which car would you buy?

3 pages  
Lecture 240 
Why would you migrate to another state?

3 pages  
Lecture 241 
Why do people commit crimes?

3 pages  
Lecture 242 
Do you eat enough?

3 pages  
Lecture 243 
Can you differentiate between a real and a fake note?

4 pages  
Lecture 244 
How hard is it to keep warm?

4 pages 
Instructor Biography
We are an Analytics firm committed to developing intellectual property that will help individuals and their organisation take smarter decisions every day. ATI, the education arm of Redwood Associates has helped 200 companies and over 15000 individuals speak the language of DATA
The founder Gautam Munshi has nearly two decades of high performance analytics experience. His strong belief that anyone can become an analyst has led him to build a team of 12 – a group of math geeks, techies, musicians, comedians, beer enthusiasts, agriculturists, geneticists, teachers and bankers,who have the gumption that they can make a difference and truly believe that analytics can influence and make a huge impact on a dayday basis. It is this diverse lot that brings Analytics to the mind space of every individual. You can view their moments in the lime light here and follow them on Facebook
Course Features
 Lectures 0
 Quizzes 0
 Duration 50 hours
 Skill level All level
 Language English
 Students 7797
 Assessments Self