Certybox offers a comprehensive and yet affordable program in business analytics using R. the program has an employment-oriented approach and is based on a detailed research of companies’ requirements. It prepares you for roles like business analyst, data analyst etc and is available in online and offline modes.

Course Description

The future of decision making will greatly rely on data, and no industry will remain untouched by this development. Data, however, has its own set of issues and challenges; for the data available to be meaningful and concise, one needs to organize it efficiently.

In the program, you will learn the nuances of data collection, data presentation, and model building using real-life datasets. You will learn how to build supervised and unsupervised machine learning models; you will be introduced to algorithms to solve classification and segmentation problems. We will also introduce you to R platform, and different algorithms which can be used in the model building activity.

At the end of the program you will develop a clear understanding of the need for business analytics and will be able to apply it to solve some interesting problems cutting across various business domains.

Program Outcome

This course is intended to give a holistic understanding on data science and its application using R platform. At the end of this program the participant would:

  • Understand key concepts on business analytics
  • Understand some of the primary algorithms used for data analysis
  • Understand and apply supervised and unsupervised machine learning algorithms
  • Understand the various sampling strategies and its efficacy in learning process
  • Gain hands-on experience in applying R on real life dataset
  • Complete a full life cycle of a project using R
  • Be aware of different packages which can be used in R for making robust and complex models

Who should take this course? 

Getting certified should definitely be considered but not limited to people in the following roles in any Industry. Business Analytics with Excel is a great course for both beginners and experienced professionals who are inexperienced or have recently stepped into the field of analytics. This course is beneficial for:

    • IT developers and testers
    • Data analysts
    • Junior data scientists
    • Analytics professionals
    • BI and reporting professionals
    • Project managers
    • Students
    • Professionals working with data in any industry

Benefits
The benefits of Business Analytics are widespread across all industries and functions, including Information Technology, Web/E-commerce, Healthcare, Law Enforcement, Banking and Insurance, Biotechnology, Human Resource Management. Some of the application areas include critical product analysis, target marketing, customer lifecycle management, customer service, social media behavior and link analysis, fraud detection, genetic research, inventory management, etc.

Below a list of a few Business Analytics roles across industries:

Data Analyst , Business Analyst, Finance Analyst , Marketing Analytics Manager , Pricing Analyst ,Supply Chain Analyst , Website Analyst , Fraud Analyst , Retail Sales Analyst, Clinical Analyst.

Program Outcome

This course will give you a holistic understanding on data science and its application using R platform. At the end of this program the participant will:.

  • Understand key concepts on business analytics.
  • Understand some of the primary algorithms used for data analysis.
  • Understand and apply supervised and unsupervised machine learning algorithms.
  • Understand the various sampling strategies and its efficacy in learning process.
  • Gain hands-on experience in applying R on real life dataset.
  • Complete a full life cycle of a project using R.
  • Be aware of different packages which can be used in R for making robust and complex models.

 Our Faculty

All of our highly-qualified trainers are certified from IIMB, with more than 15 years of experience in training and working professionally in the field. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation and live training demonstration before they are certified to train for us. We also ensure that only those trainers who maintain a high alumni rating continue to train for us.

DELIVERABLES

  • Real-life Case Studies- Live project based on any of the selected use cases, involving the implementation of Data Science.
  • Coverage- Comprehensive coverage on various analytical tools like R, SAS, Hadoop, etc.
  • Advanced Analytics: Learn Text Analytics, Marketing Analytics and Retail Analytics
  • Online Material: 24*7 accesses to practice material, videos, quizzes, mock tests, etc., to ensure learning efficiency.
  • 24 x 7 Expert Support- Expert faculty with wide industry experience in the Analytics industry and alumni of top universities
  • Mentoring: Get mentoring from data scientist working in leading companies such as Mckinsey, Deloitte, Mu Sigma, Google, PWC etc.
  • Lifetime Access- You get lifetime access to the Learning Management System (LMS). Class recordings and presentations can be viewed online from the LMS.
  • Placement assistance: Candidates will receive 100% placement assistance which includes interview grooming, resume writing etc.

BUSINESS ANALYTICS COURSE CERTIFICATION PROCESS

Once you have successfully submitted the BUSINESS ANALYTICS Certification project, it will be reviewed by our expert panel. After a successful evaluation, you will be awarded BUSINESS ANALYTICS Expert Certificate. Our certification has industry-wide recognition and we are the preferred Training partner for many MNCs including Cisco, Ford, Mphasis, Nokia, Wipro, Accenture, IBM, Philips, Citi, Mindtree, BNYMellon and many more.

Course Curriculum

Data Science Foundations
Introduction to Business Analytics 00:00:00
Introduction to R programming
Fundamentals of R | Reading Data Files, Data Manipulation 00:00:00
Statistics with R 00:00:00
Data Manipulation and visualization using real life dataset 00:00:00
Machine Learning using R
Inferential Statistics |Hypothesis Testing, ANOVA, etc 00:00:00
Classification | Logistic Regression, Decision Trees etc 00:00:00
Predictive Modelling| Linear Regression 00:00:00
Clustering or Segmentation |K-means and Hierarchical 00:00:00
Forecasting | Time series 00:00:00
Real life projects*
Retail Analytics 00:00:00
Healthcare Analytics 00:00:00
Finance and Risk Analytics 00:00:00
Marketing Mix Modelling 00:00:00
Churn Prediction|Attrition Management 00:00:00
Credit Rating. 00:00:00

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  • $700
  • 180 Days
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