About The Course
This Data Science course will cover the whole data lifecycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modeling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities.
After the completion of the Data Science course, you should be able to:
- Gain insight into the 'Roles' played by a Data Scientist
- Analyse Big Data using R, Hadoop and Machine Learning
- Understand the Data Analysis Life Cycle
- Work with different data formats like XML, CSV and SAS, SPSS, etc.
- Learn tools and techniques for data transformation
- Understand Data Mining techniques and their implementation
- Analyse data using machine learning algorithms in R
- Work with Hadoop Mappers and Reducers to analyze data
- Implement various Machine Learning Algorithms in Apache Mahout
- Gain insight into data visualization and optimization techniques
- Explore the parallel processing feature in R
Who should go for this course?
The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques to Big Data. The following professionals can go for this course:
- Developers aspiring to be a 'Data Scientist'
- Analytics Managers who are leading a team of analysts
- SAS/SPSS Professionals looking to gain understanding of Big Data Analytics
- Business Analysts who want to understand Machine Learning (ML) Techniques
- Information Architects who want to gain expertise in Predictive Analytics
- 'R' professionals who want to capture and analyze Big Data
- Hadoop Professionals who want to learn R and ML techniques
- Analysts wanting to understand Data Science methodologies
There is no specific pre-requisite for the course, however, exposure to core Java and mathematical aptitude will be beneficial. Edureka will provide you complimentary self-paced courses covering essentials of Hadoop, R, and Mahout to brush up the fundamentals required for the course.
Why Learn Data Science?
Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.
The following blogs will help you understand the significance of Data Science training:
Which Case-Studies will be a part of the Course?
Towards the end of the Course, you will be working on a live project. Here are the few Industry-wise case studies e.g. Finance, Retail, Media, Aviation, Sports etc. which you can take up as your project work:
Project#1: Flight Delay Prediction
Description : The goal of this project is to predict the Arrival Time of a flight given the parameters like:"UniqueCarrier", "DepDelay", "AirTime", "Distance", "ArrDelay", etc. Whether these attributes affect the arrival delay and if yes, to which extent? Construct a model and predict the arrival delay. Compute the (Source Airport - Destination Airport) mean scheduled time, actual and inflight time with the help of MapReduce in R and visualize the results using R.
Project #2: Stock Market Prediction
Description: This problem is about making predictions on the stock market data.The dataset contains the daily quotes of the SP500 stock index from 1970-01-02 to 2009-09-15 (10,000+ daily sessions). For each day information is given on the Open, High, Low and Close prices, and also for the Volume and adjusted close price.
Project #3: Twitter Analytics
Industry: Social Media
Description: This problem is about social media analytics. This can be defined as Measuring, Analyzing, and Interpreting interactions and associations between people, topics, and ideas. The dataset to be analyzed is captured by Live Twitter Streaming. This problem is mainly about how to use Twitter analytics to find meaningful data by performing Sentiment analysis of the tweets obtained and visualizing the conclusions.
Project #4: Recommendation System
Description: The problem of creating recommendations given a large data set from directly elicited ratings is a potential area which was lately boosted by players like Amazon, Netflix, Google to name a few. In this project, you are given a collection of real-world data from the different users involving the products they like, rating assigned to the product, etc. and you have to create and come up with recommendations for the users.
Project #5: NFL Data Analysis
Description: The dataset is a set of tweets by fans from an NFL game. This project is about analyzing the tweets posted by football fans all over the world on the NFL tournament semi-finals and finds out insights like top 10 most popular topics being discussed, most talked about team etc.
Online Classes: 30 Hrs
There will be 10 instructor-led interactive online classes during the course. Each class will be approximately 3 hours and will happen at the scheduled time of the batch you choose. You have the flexibility to reschedule your class in a different batch if you miss any class. Class recordings will be uploaded in the LMS after the class. Lifetime access to class recordings.
Assignments: 40 Hrs
Each class will be followed by practical assignments which can be completed before the next class. These assignments will help you to understand the concepts taught in Data Science better. Our 24x7 expert support team is available to help you through email, phone or Live support for any issues you may face during the Lab Hours.
Project: 20 Hrs
Towards the end of the course, you will be working on a project where you are expected to implement the techniques learned during the course to visualize and analyze data.
You get lifetime access to the Learning Management System (LMS). The Class recordings and presentations can be viewed online from the LMS. The installation guides, sample codes and project documents are available in the downloadable format in the LMS. Also, your login will never get expired.
24 x 7 Support
We have a 24x7 online support team available to help you with any technical queries you may have during the course. All the queries are tracked as tickets and you get a guaranteed response from a support engineer. If required, the support team can also provide you Live support by accessing your machine remotely. This ensures that all your doubts and problems faced during labs and project work are clarified round the clock.
Towards the end of the course, you will work on a project. Edureka certifies you in Data Science course based on the project reviewed by our expert panel. Anyone certified by edureka will be able to demonstrate practical expertise in Data Science.
This school offers programs in:
Last updated February 14, 2018