Course Review – PG Program in Data Science and Business Analytics-1 by McCombs School of Business
The programme offers to cover end-to-end detailed concepts on the fundamentals and advanced topics in data science. This makes the program a good fit for beginners as well as mid-level professionals. The programme offers experiential learning, which suggests that this course is constructed to transform candidates into business-ready Data Science and analytics professionals through hands-on experiential understanding of relevant tools. This is accomplished through hands-on labs, practice assignments, hackathons, quizzes, and tasks on software packages such as R, Tableau, SAS (online), and Python. Data Science and business analytics form key components of this course
Highlights
URL | https://www.mygreatlearning.com/pg-program-data-science-and-business-analytics-course-lvc |
Mode of Learning | Online |
Duration | 11 Months |
Fee | Rs. 3,35,000 +GST |
Key Features
The Post Graduate Program in Data Science and Business Analytics programme covers 132 hours of learning in 11 months with live classes on weekends. This makes it easier for candidates to manage their current commitments along with polishing their skills through this programme. The applicants also get the opportunity to listen to distinguished speakers from leading companies and assimilate the best practices discussed by them in their sessions. The capstone project covers a large-scale range of skills to emphasize applied learning. The program extends to two major skills including visualization and specific domain exposure such as Data science implications on Marketing, Finance, Social Media, Operations, and Supply Chain.
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Content coverage: The course is divided into four major modules to provide a comprehensive course coverage of Data Science and Business Analytics. The programme is strategized by building a foundation and then moves on to Data Science techniques and Visualisation insights following all the way to domain exposure.
Mode of Learning: The programme is completely online with 132 hours of live learning and 225+ hours of learning content in the form of recorded videos. The project offers eight real-world graded assignments and 16+ real-world case studies.
Target Audience: The programme focuses on beginners and mid-level professionals who aspire to excel in Data Science and Business Analytics.
Learning support: The programme covers E-portfolio support, resume building, and interview preparation along with career guidance.
Price Aid: Candidates can avail zero interest EMI options from multiple organizations.
College pedigree: The University of Texas at Austin’s McCombs School of Business holds a strong college pedigree and a history of a strong alumni network. The college is ranked second for its Master of Science in Business Analytics (MSBA) degree in 2018.
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What makes the course unique
The program is designed to offer industry-relevant skills and expertise. The programme brings forth a curriculum that combines academic refinement and business significance to facilitate participants in understanding the basics of management, Data Science techniques, and applications for data-based decision making. Hence, it aims to provide an end-to-end learning application, where a candidate would work with data as well as the work on the next steps of data analytics such as visualisation and business intelligence.
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Course Offering
The following points cover the chief offerings by the certification.
The course is structured, delivered, and endorsed by prominent analytical, technology, and consulting organizations.
Peer collaboration prospects for exchanging job referrals and interview tricks.
A comprehensive two-month capstone project mentored by an industry expert.
Dedicated career support through interview training and resume-building conferences.
Eight industry-relevant graded projects and 16+ real-world case studies.
Key discussion points
Value Addition: Career guidance and college pedigree, applied learning opportunities, a certificate from Texas McCombs university and GL India, hands-on learning (detailed) case studies.
Points to debate: The program lacks any form of fully-funded scholarship. However, it furnishes a range of payment options. The programme also does not offer any long-term executive alumni status.
Career Options
Data Analyst: A Data Analyst is responsible to leverage industry-relevant data to discover patterns or solve complex business problems. Their profile and responsibilities are divided into a range of activities such as helping out in setting up the entire data pipeline to problem-solving using data and algorithms. They must be able to leverage multiple algorithms and also understand which algorithm offers the best accuracy for their data type. They must also work on business Intelligence and visualization to support complementary data-based decision-making activities.
Data Consultant: A Data Consultant is expected to be a jack of all trades across data touchpoints. They must work on setting up the entire data strategy and the data architecture. They work in parallel with data analysts and data engineers to understand how data management would work across the enterprise. Their duties span across data architecture, data engineering, visualization, and business intelligence. They would also work on the best strategies for data storage and how the data would be used across use cases within the organization.
Business Intelligence lead: A business Intelligence Lead would need to understand the entire landscape of how data-backed decision-making works across his/her particular domain. They must leverage domain knowledge and map it across data technologies to bring about an efficient solution to life. They work towards market research and market intelligence to understand how data intelligence is shaping up their industry.
Business Analyst: A Business analyst acts as a bridge between the functional and the technical teams. They must understand the business requirement as well as the technical architecture of the system to support product or serving building. They would need to understand the technical feasibility of a functional solution as well as the scope for scalability and change management within a product or a service. Their work spans across the technical and the functional domain to bridge the gap between industry-relevant knowledge and technology-specific abilities.
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