The Data Science with R course focuses on imparting in-depth knowledge of various techniques for data analytics using R. The course includes real-life projects, case studies, and includes R CloudLabs for practice.
Master R language: The course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various packages available in R.
Master advanced statistical concepts: Learn various statistical concepts like linear and logistic regression, cluster analysis, and forecasting with predictive data analytics. You will also learn hypothesis testing techniques.
Case Study Based Project: As a part of the course, you will be required to execute real-life projects using CloudLab. There are four case study based projects.
This course will enable you to:
- Gain a foundational understanding of business analytics
- Install R, R-studio, and workspace setup. You will also learn about the various R packages
- Master the R programming and understand how various statements are executed in R
- Gain an in-depth understanding of data structure used in R and learn to import/export data in R
- Define, understand and use the various apply functions and DPLYP functions
- Understand and use the various graphics in R for data visualization
- Gain a basic understanding of the various statistical concepts
- Understand and use hypothesis testing method to drive business decisions
- Understand and use linear, non-linear regression models, and classification techniques for data analysis
- Learn and use the various association rules and Apriori algorithm
- Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering
Introduction to the Concepts of Data Analytics and RModule 2:
R Data structuresModule 3:
Using R for StatisticsModule 4:
Data VisualizationModule 5:
Data ManipulationModule 6:
Introduction to Machine Learning, DRTModule 7:
Clustering, MBAModule 8:
Linear, Logistic regression with RModule 9:
Decision Tree,Naïve BayesModule 10:
SVM,NN,Ensemble LearningModule 11:
Project ExplanationModule 12:
Time series Analysis with RModule 13:
Text Analytics with R
Instructors are handpicked from a selected group of industry experts and mentors and trained to deliver the best online learning experience. All training.com instructors have at least ten years of industry experience and extensive functional expertise in the field they train.
An assessment will be conducted at the end of the course. On completion of the assessment with a minimum of 70% marks, training.com will issue a certificate of successful completion from NIIT.
Learners can re-attempt the assessment for a maximum of five attempts.
A Participation certificate will be issued if the learner does not score 70% after five attempts.
Learner should have basic knowledge of statistics and computer programming. Preferably a reasonable level of proficiency in any data handling tool like MS Excel.
What is the Case Study based Project which I need to develop as part of this program?
Background: A finance company deals in all home loans. They have presence across all urban, semi urban and rural areas. Customer first applies for home loan after that company validates the customer eligibility for loan.
Problem: Company wants to automate the loan eligibility process (real time) based on customer detail provided while filling online application form. These details are Gender, Marital Status, Education, Number of Dependents, Income, Loan Amount, Credit History and others. To automate this process, they have given a problem to identify the customers segments; those are eligible for loan amount so that they can specifically target these customers. You are required to use your “R” skills to deliver a model for predicting loan eligibility of a customer. In other words, you will tell the company by your solution that whether customer applied for loan will default or not in future!
Why should I join this course?
The term “data scientist” is the most happening and the hottest job title in the IT field. Starting salaries match upto $100,000, which is 22% more than other job roles (Source: http://www.burtchworks.com ). R programming is the best tool for most jobs that involve data. It is the most popular programming language that data scientists use. It is in heavy use at several large organisations like Microsoft, Google and Facebook. R programming in academia is important because it creates a pool of talent that feeds the data industry. The best way to learn R is by doing. This course is designed to master various R programming concepts for data analytics by implementing various real-life and industry-based projects.
Where can I find my session schedule?
The session schedule will be available in the training.com Student portal - Learning Plan section. You can login to your training.com account to view the same.
What is your refund policy?
Upon registering for the course, if for some reason you are unable or unwilling to participate in the course further, you can apply for a refund. You can initiate the refund any time before start of the second session of the course by sending an email to firstname.lastname@example.org , with your enrolment details and bank account details (where you want the amount to be transferred). Once you initiate a refund request, you will receive the amount within 21 days after confirmation and verification by our team. This is provided if you have not downloaded any courseware after registration.
What are the minimum system requirements to attend the course?
- Personal computer or Laptop with web camera
- Headphone with Mic
- Minimum 1 Mbps broadband connection with 4 Mbps download speed
Minimum system requirements for accessing the courses are:
A self-diagnostic test to meet necessary requirements to be done is available at
Please note that webcam, mike and internet speed cannot be verified through this link.
Is there an official support desk for technical guidance during the training program?
Yes. For immediate technical support during the live online classroom sessions, you can call 91-9717992809 or 0124-4917203 between 9:00 AM and 8:00 PM IST. You can write to email@example.com for all other queries and our team will be happy to help you.