Analytics For All
3.9 (114 ratings)
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Analytics For All

Your practical application oriented guide to analyzing Big Data
3.9 (114 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
2,034 students enrolled
Last updated 4/2017
English
Current price: $10 Original price: $100 Discount: 90% off
5 hours left at this price!
30-Day Money-Back Guarantee
Includes:
  • 15 hours on-demand video
  • 5 Articles
  • 21 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Application oriented course
  • Participants gain hands on experience in dealing with data
  • Focus on foundational aspects of statistics and predictive modelling techniques
  • WORK ON EXCEL! And by that we mean - Organize and interpret information easily - Reformat and rearrange data - Process data - Use graphs and charts - Work on Pivot tables
  • Learn to implement Data Manipulation, Data management and Textual Analytics Basics through R
View Curriculum
Requirements
  • Working installation of R. The R/R Studio Download is available at cran.r-project.org
  • All students need to do is make sure they have MS Excel 2007 or a later version installed on their system. We will take care of the rest!
Description

This course helps you learn simple but powerful ways to work with data.

It is designed to be help people with limited statistical or programming skills quickly become productive in an increasingly digitized workplace.

In this course you will use R (an open-sourced, easy to use data mining tool) and practice with real life data-sets.

We focus on the application and provide you with plenty of support material for your long term learning.

It also includes a project that you can attempt when you feel confident in the skills you learn.

Who is the target audience?
  • Beginner level - High school math knowledge is all you need
  • Anyone who faces a mounting data load at their workplace
  • Well, anyone who is interested to use Excel in their work, in their business or to get a job. This is a great course for an absolute beginner in Excel to anyone who is a whiz in Excel, and just wants to brush up on long forgotten concepts!
  • Anyone who is into analyzing data! R is a great open source tool used globally. It makes data analysis and Text Analytics really easy. So, any serious Analytics professional would do well to become an expert at it.
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Curriculum For This Course
173 Lectures
15:51:36
+
Welcome
4 Lectures 06:18

In this course you will cover 4 Data mining techniques which will be explained using case studies using R programming language. So you will need to install R-Studio before you start off-this course.

The 4 techniques that will be covered are:

    ·Liner Regression – It is a predictive model. For example it could be used to predict the sales for next month

    ·Logistic Regression-Another predictive model used for classification tasks

    ·Cluster Analysis- this is less statistical and more algorithmic in nature. It is used to find similar records. A common application would be how ecommerce sites give recommendations to customers

    ·Factor Analysis- a nice tool to reduce sizes of data-sets

The installation guide is included in the supplementary material

Preview 01:24


Please find the downloadable course material in the below link


https://www.analyticstraining.in/course-material/

Course Material For AFA
00:02

Pretest: Find out how much you don't know !
4 questions
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Hypothesis Testing
14 Lectures 54:32



The basics-High School Math you've probably forgotten
02:56

Mean and Medians
06:20

Probability: The reason you probably haven't won the lottery
06:07

ANOVA: Your car brand and your dinner bill
03:10

T Stat- Your first new Statistic
06:33

Example
06:35

1 sample t test- Checking Means
04:30

2-sample T test: Does TV make you buy things?
04:22

Chi Square TOI: One Category on another
03:06

Cheat Sheet: So you don't have to remember all of it
02:49

Questions you might have.
00:13

Understood it all?
3 questions

Check your Understanding
5 questions
+
Linear regression
9 Lectures 15:50
Pedagogy
2 pages

What is a predictive model?
01:00

Building your first model using R
02:49

Step 2: Use the lm function
02:02

Step 3: Split your data
01:29

Step 4: Model selection
02:49

Step 5: Multicollinearity
02:09

Predictions and quality checks
03:32

FAQ
1 page

Check your Understanding
5 questions
+
Logistic Regression
10 Lectures 30:22
How to spot dissatisfied customers
04:50

The math behind it
03:00

Building a logistic regression using R
01:10

Step 1: Import your data
02:14

Step 2: Use the "glm" function to build a model
03:15

Step 3: Split your data
01:36

Step 4: Model selection
03:16

Step 5: Make your predictions
04:39

Step 6: Checking your model performance
06:22

FAQ
1 page

Check your Understanding
5 questions
+
Cluster analysis
8 Lectures 15:06
Segmenting data with K-Means algorithm
00:51

Import your data
01:37

Specify number of clusters
03:15

Interpret your cluster output
04:48

FAQ
1 page

Where do we use factor analysis
01:11

#########################################################################################

Note on factor analysis using the factanal() function in R:

The method factanal is a maximum likelihood algorithm, and is not always guaranteed find an optimum solution. Sometimes, it will return the "unable to optimize from this starting value" error. This can sometimes be fixed by increasing the "opt" value, and sometimes by increasing the "maxit" value (in the "control" parameter in the function). If you face this problem, you may try out these options, but be aware that not every method will return an optimum solution for any given data set.

############################################################################################

FACTANAL READ ME
00:25

Using R for factor analysis
02:59

Check your Understanding
5 questions
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Factor analysis
3 Lectures 06:36
Computing factor loadings
05:09

Scoring survey
01:27

FAQ
1 page

Check your Understanding
5 questions
+
Project
1 Lecture 00:00
Elections data
11 pages
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Advanced reading
1 Lecture 00:00
How cluster analysis is at the heart of Amazon's business model
5 pages
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DATA CHALLENGE - Work That Data
6 Lectures 12:46
THE RULES
3 pages

Data Set 1: Meteorite Data
1 page

How good are you with choosing the right flower?
12:27

Data Set 2: Groundwater Depletion Rates
00:04

Data Set 3: Exam Data
00:15

Which car would you buy?
3 pages
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DATA CHALLENGE
2 Lectures 00:00
RULES of the GAME
1 page

Titanic Data Set
2 pages
26 More Sections
About the Instructor
ATI - Analytics Training Institute
3.9 Average rating
236 Reviews
8,905 Students
13 Courses
Committed to creating a difference

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 day-day 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