quick glance
• Course duration: 32 weeks, 10 hours/week
• Learning mode: Instructor-led
•  72000 2000 (Instructor-led)

Plus taxes, as applicable

Who should do this course?
This course is meant for anyone interested in a career in Big Data, IT or database professionals looking to specialise in Big Data, analytics professionals who want to broaden their skills in Big Data, and students or graduates aiming to build a career in Big Data and Analytics.
What are the pre-requisites?
Knowledge of Java or OOPS programming languages is preferable but not mandatory. We also give free access to introductory Java programming videos.

Recommended: Ability to work with Unix/Linux Platforms.
01Introduction to Analytics
02Statistical Concepts and their application in business
03Basic Analytic Techniques
04Predictive Modeling Techniques
05Putting the Jigsaw Together
10Big Data Case Studies
Every case study involves hands-on work on large business data sets in the Jigsaw Lab.
01
Determine the best Indian cricketer
• Determine who the is best batsman among Tendulkar, Dravid and Ganguly (players of the Indian cricket team), using regression analysis.
02
Predicting the price of a car
• Predict the price of a car based upon variables like model, make of the car and engine capacity among others. The data set has 12 columns. To predict the target variable multiple linear regression is used. The model is then analysed further to improve the model performance.
03
Customer behaviour on a loan
• Using bank data with 21 columns the objective is to predict the defaulting behaviour of a customer. The data is analysed by logistic regression as well as using decision trees giving the insights and comparison for both the techniques.
04
Analysis of grocery sales in different stores in Karnataka and Tamil Nadu
• The analysis is on the mix of sales by category and average sales per square foot of space for a grocery retailer with 515 stores.
05
Predicting the money bet on a horse race
• The aim of this study is to come up with recommendations to a client who is in the horse racing industry on how to maximize money bet on any race. Insights are generated from data having 23 columns with different track types and years in which the races were conducted.
06
Analysis of customer attrition in the telecom industry
• The goal of the study is to analyse customer attrition based upon minutes used, age and other demographic information.
07
Performing sentiment analysis on tweets in the context of Indian politics
• Use extracted Twitter information (15,000 tweets related to the keyword "AAM AADMI PARTY" over a period of one week in end December 2013) to estimate an overall positive or negative perception in the opinions being expressed by people.
08
• Analysis of over 1 million tweets and 15 columns of information. This case study will use the Flume component of Hadoop to collect almost a gigabyte of Twitter data.
09
Clickstream Analytics using Web Data
• Clickstream data is an information trail a user leaves behind while visiting a website. These data files contain information around URL, timestamp, IP address, data and a unique user ID over a range of 5 million rows.
10
Financial Analysis on stock market data
• Analysis of the New York Stock Exchange data containing over 5 million rows and 10 columns for about 2500 firms.
11
Flight Delay Optimization using Airline Data
• Analysis of airlines data with over 123 million rows (observations) and 29 columns containing variables of different data types including factors with lots of levels.
12
• Analysis of an email corpus containing data of about 150 users and a total of about 500,000 messages.
Instructor-led Classes
• Instructor-led, interactive classes conducted by analytics experts in a virtual classroom.

The Advanced Specialization in Big Data Analytics course comprises 32 instructor-led sessions of 2 hours each.

Recordings of instructor-led classes
• All instructor-led classes are also recorded, and participants get access to recordings to review the material or to make up for any missed Q&A sessions.

Pre-recorded video lectures
• Pre-recorded video lectures can be viewed at any time and as many times as the participant wants.

You will have access to about 50 hours of pre-recorded video lectures & 64 hours of pre-recorded classroom training.

Jigsaw Learning Centre
• Access to a variety of supplemental resources including hand outs, reference material, guides, lecture transcripts and student forums for a period of 15 months.

Offline Support
• Access to the Jigsaw Faculty via email, phone or chat for a period of 15 months.

Q&A Sessions
• Instructor-led sessions conducted by analytics mentors to resolve questions and doubts.

The Advanced Specialization in Big Data Analytics course inclues 2 hours of Q&A every month.

Jigsaw Lab
• Access to the Jigsaw Lab, a unique cloud-based solution, for hands-on experience on large business data sets using analytics tools for a period of 15 months.

Career Assistance
• Access to career assistance service includes resume building, interview preparation and identification of relevant opportunities.

01
What is the duration of the course?
• The duration of the instructor led course is 28 weeks. You will have 12 months to complete the course.

02
Will I get a chance to work with huge datasets?
• You will work on multiple case studies as part of the course. The case studies will involve hands-on work with huge datasets.

03
Do you provide placement assistance?
• Yes, we provide placement assistance to our students as well. Learn about Jigsaw's placement support here.

04
What is the refund policy?
• We like to keep our students happy, so we have a 7-day no questions asked refund policy.

05
How much Java do I need to know?
• Knowledge of Java or OOPS programming languages is preferable but not mandatory. We also give free access to introductory Java programming videos.

06
Do I need to know R?
• We teach R from scratch.

07
What are the pre-requisites for the course?
• Knowledge of Java or OOPS programming languages is preferable but not mandatory. We also give free access to introductory Java programming videos.

What is recommended is an ability to work with Unix/Linux Platforms.

08
What are the core benefits of this course?
• After completing this course you will acquire expertise with statistical concepts, data mining techniques, predictive analytics skills, understanding of big data technology and hands on experience with analytical tools. You will also acquire expertise with Hadoop and technologies used with Hadoop, and R. You will get hands-on experience with setting up and processing Big Data using a Hadoop cluster, and performing analytics with R through practice assignments with real life business datasets.

09
Will I have hands-on experience in using these tools?
• Yes. You will have 24X7 access to the Jigsaw Lab for 12 months to practice all the tools.

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