CERTIFICATE IN BUSINESS ANALYTICS FUNDAMENTALS

Description

This is an analytics foundation course. The course will equip participants with the essential skills required to prepare for a career in business and data analytics. This course also prepares the participants for subsequent learnings in the core analytics areas of building models to solve different problems, whether in business, technical or research domains. It is part of the Foundation layer in SetConnect’s fasTrac™ methodology.

Key Takeaways

At the end of the programme, you will be able to:

  • Translate business requirements to problems that can be solved computationally
  • Write scripts using syntax and conventions established in industry best practices
  • Develop a fully functional programme using industry-relevant Python
  • Prepare for additional courses to build your career in Analytics and Data Science

Why Business Analytics

Business analytics is a fast-growing field that explores the methods of understanding data within an organization to improve decision-making. By building capability and expertise in analytics companies are able to evaluate the data they have and the data required to manage the business. This programme equips participants with the essential skills needed to prepare for a career in Analytics and Data Science. These include descriptive statistics, hypothesis tests, confidence intervals and linear regression. Learners will also have the ability to apply statistical methods and task automation for problem solving using Python.

Pedagogy

 

[Average learning hours per week – live, recorded, assignments]

  • Blended learning: The courses are delivered as a combination of live classroom (synchronous learning) and recorded sessions (asynchronous learning)
  • Global faculty: The faculty team consists of well qualified, highly experienced instructors from the US, UK and India
  • Industry interaction: Interact with senior global industry experts
  • Experiential learning: The courses are supported by mentored hands-on practice sessions, activities and projects
  • Analytics in Practice: Opportunity to define, solve and apply analytics to an appropriately scoped industry problem working as a student-consultant at a sponsoring organization.

GLOBAL FACULTY PANEL

Dr Ramesh Rajagopalan
Dr Novin Ghaffari
Mr. Gurudutt Shenoy
Dr Bugra Alkan

SUPPORTED BY RVIM COE

Dr. Purrushottam Bung
Dr. Bikramaditya Ghosh
Dr. Santhosh M
Prof. Dileep
Prof. Vandana Gablani
Prof. Nagasubba Reddy
Prof. Shreya Shankar
Duration : 9 weeks
Benefits
  • Prepare yourself for potential roles as a business analyst, business intelligence analyst, data analyst, data technician or operations analyst
  • Learn directly from global faculty who have rich experience and subject matter expertise
  • Become proficient with in-demand skills and open-source technologies
  • Formulate and solve business problems with statistical analysis

Who is it for?

This course is relevant for under-graduates, fresh graduates and working professionals seeking to enter the field of Analytics and Data Science. No prior work experience is required.

What will participants be able to achieve at the end of this programme?

  • Proficiency with industry-relevant Python programming to manipulate data sets

  • Ability to formulate questions that may be solved through statistical analysis

  • Perform data analysis applying statistical methods

  • Gain an appreciation of popular careers in Analytics and Data Science

How will participants benefit?

  • Build an essential foundation in preparation for subsequent Analytics and Data Science programmes

  • Identify available careers in the field and skills required to enter into these careers

  • Learn directly from global faculty who have rich experience and subject matter expertise

  • Formulate and solve business problems with statistical analysis

  • Prepare for potential roles as a business analyst, business intelligence analyst, data analyst, data technician or operations analyst

Duration

  • Duration: 10 weeks, 80 hours

  • 20 hours synchronous, 20 hours asynchronous

  • 40 hours Lab and practice sessions

  • On an average, you should plan to spend between 10-12 hours per week

Schedule

  • Programme commencement: August 30, 2021

  • Last date for application – Sept 1, 2021

  • Programme Completion – November 6, 2021

Programme Details

Who is it for?

This course is relevant for under-graduates, fresh graduates and working professionals seeking to enter the field of Analytics and Data Science. No prior work experience is required.

What will participants be able to achieve at the end of this programme?

  • Proficiency with industry-relevant Python programming to manipulate data sets

  • Ability to formulate questions that may be solved through statistical analysis

  • Perform data analysis applying statistical methods

  • Gain an appreciation of popular careers in Analytics and Data Science

How will participants benefit?

  • Build an essential foundation in preparation for subsequent Analytics and Data Science programmes

  • Identify available careers in the field and skills required to enter into these careers

  • Learn directly from global faculty who have rich experience and subject matter expertise

  • Formulate and solve business problems with statistical analysis

  • Prepare for potential roles as a business analyst, business intelligence analyst, data analyst, data technician or operations analyst

Schedule

Duration

  • Duration: 10 weeks, 80 hours

  • 20 hours synchronous, 20 hours asynchronous

  • 40 hours Lab and practice sessions

  • On an average, you should plan to spend between 10-12 hours per week

Schedule

  • Programme commencement: August 30, 2021

  • Last date for application – Sept 1, 2021

  • Programme Completion – November 6, 2021

Topics

List of Courses

Python for Data Analytics

This is the first course in the Foundation layer in SetConnect’s fasTrac™ methodology. The fundamental programming concepts includes an introduction to data types, manipulating strings, control structures, error handling and working with arrays. You will be able use libraries and develop simple scripts which are used in building applications. This course will equip you with information on coding standards, so that you will be able to confidently write Python scripts aligned with industry best practices.

The lessons in the Python for Data Analytics course will help you:

  • Review the essential and advanced concepts for analytics
  • Follow the instructor’s illustration of detailed coding
  • Appreciate the best practices for developing code
  • Carry out practice assignments in coding
  • Use powerful libraries to develop solutions for a wide range of mathematical and statistical techniques

In addition, you will also be able to develop fully functional programmes using a Python interpreter. You will learn how to:

  • Install Python
  • Develop, troubleshoot and execute scripts
  • Access common libraries relevant to Analytics
  • Resolve script errors
  • Validate user inputs in programme development

Business Statistics with Python application

This is the second course in the Foundation layer in SetConnect’s fasTrac™ methodology. We recommend that you complete the first course, Python in Data Analytics before taking this course. In this course, you will learn real-world modelling applications using statistical methods. By learning how to frame these applications in statistical frameworks, you will learn how to solve statistical problems using technology and apply the results to real-world business problems. Thus, this course provides a rigorous statistical foundation for those aspiring for analytical roles that demand in-depth analyses of large data sets.

The lessons in the Business Statistics for Python application course will help you:

  • Review the essential and advanced concepts related to Business Statistics
  • Follow the instructor’s illustration of statistical examples
  • Be aware of both the applications and limitations of different statistical techniques
  • Carry out practice assignments in applying Python to statistical problems
  • Use popular Python libraries to develop solutions for a wide range of statistical techniques

Upon completing this course, you’ll be able to:

  • Formulate real-world data analysis questions as problems in statistical frameworks
  • Understand the role of statistics in doing the research
  • Read and understand the statistical concepts from reports and papers
  • Master the statistical methods to summarize and analyse data: descriptive statistics, confidence interval for population mean and proportion, hypothesis testing, Chi-square test for independence, linear regression model.
  • Interpret results from various computer packages and be able to perform appropriate statistical techniques