Course Review - Advanced Management Programme in Business Analytics by ISB

This advanced certification course focuses on industry relevant skills and in-depth knowledge of business analytics and its complementary skills. Business Analytics is fast becoming an essential part of business operations. Organizations of all sizes have realized its vast ability to unlock insights and improve business decisions across verticals. This business analytics course takes a comprehensive approach beginning with establishing the data strategy then moving on to analytics and finally focusing on the dashboarding techniques, required to make sense of Data and for effective decision-making. The business analytics course is a must for those who are interested in taking up mid-level to senior management roles. Also, this Isb business analytics review has been done by an expert which makes it even more apt for students to go through before making a selection.

Highlights

Key Features

The Advanced Management Programme in Business Analytics comprises an impeccable pedagogy and curriculum design. The programme emphasizes foundational projects right from the beginning and offers two detailed hands-on case studies as well as a large-scale comprehensive capstone project. These projects provide much-needed insights to students looking to gain pragmatic industry-relevant skills, which is the need of the hour. The programme sets the foundation with data management and visualization and then moves on to Machine Learning and Deep Learning. After the theoretical sessions, the sessions that follow lay special emphasis on the application of these cutting-edge technologies. Students are also offered an alumni status at the end of the programme which is a big add-on for career transition and growth.

Content coverage: The content is among the most comprehensively designed curriculums which include Data management, ML, and DL.

Mode of Learning: The programme has a mix of online and offline learning. Applicants will typically be on campus for a five-day schedule of classroom learning every alternate month for 12 months, which would preferably be planned to include a weekend. Out of the total 400 hours of learning, 240 hours are in the form of classroom learning.

Target Audience: The programme is targeted towards early to mid-level professionals who are willing to develop a profile in the business analytics domain.

Learning support: Since the programme comprises 240 hours of classroom learning, it offers a good avenue for peer learning and doubts solving sessions as well. Apart from these, the program offers alumni status and networking avenues for growth and career building.

Price Aid: The programme lacks fully funded scholarships. However, one might opt. for employee scholarships or EMI options from the various growing list of financial institutions.

College pedigree: ISB Hyderabad, holds a strong college pedigree and alumni network. ISB has been consistently ranked among the top institutions for its MBA programme. The college is known for its applied learning and expert industry faculty members to impart high-quality education.

What Makes the Course Unique

The curriculum includes two detailed hands-on projects at the beginning and a capstone project at the end which covers the most complex scenarios and trains a candidate to gain industry ready skills. The programme offers great networking avenues and an alumni status which is a great add-on to one’s resume. The offline teaching structure provides a good mix of learning and doubt solving sessions as well as acts as a platform for peer learning.

Course Offering

The following points cover the major offerings by the certification.

• 400 hours of total learning and 240 hours of immersive classroom learning

• 1140+ strong alumni network interaction and alumni status

• Advanced management program certificate directly from ISB

• Interaction with industry experts and alumni round table

• Hands-on learning with 2 projects and 1 capstone project designed to cover all aspects of business analytics

Key Discussion Points

Value Addition: Strong college pedigree, comprehensive course coverage, alumni status, and a good blend of online and offline offerings from 30+ modules.

Points to debate: The program lacks any fully funded scholarship offerings, but compensates it with easy (EMI) payment options. Lack of online peer learning or doubt solving portals and lack of support towards resume building and interview preparation.

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Career Options

AI consultant: An AI consultant must have a broad range of skills within the AI domain. As we know that data forms the core of AI, the consultant must have understood the nuances of data management and data strategy. They must advise and implement multiple use cases that we see within today's organizations which can be easily solved using AI and its complementary technologies.

AI Developer: An AI developer is expected to be skilled in multiple streams within the AI domain. The streams could be complimentary such as Machine Learning and analytics or supportive such as text analytics and speech analytics. There are a host of such streams where an AI dev. needs to work on bringing an enterprise solution to life. Common skills such as Python coding, analytics, and data management fall right at the center of an AI developer's profile.

Business Analyst: Data analytics combined with data-backed decisions forms the core of business analytics. A Business Analyst professional must act as a bridge between the functional and the technical teams to bring a product or service to life. They must analyze the technical and business challenges and must aim to bridge the gap between technology and applied business technology. Using these skills they must advise on the actual usage of technology to solve business problems and derive business values.

Business Intelligence Analyst: Data management and visualization form the foundation of business intelligence. Today’s modern organizations are all leveraging data-backed decision making and the role of a BI analyst takes center stage in such scenarios. They must analyze the business domain and then map it with the available technologies to solve a host of complex problems and develop solutions that derive long-term value.

Data Science Manager: A Data Science Manager is responsible for leveraging data for effective problem solving. Essential questions such as the type of algorithm, data pipeline, visualization, data storage and categorization are all answered by the team of data scientists who work under the Data Science Manager. He/She is expected to have a host of skills that are capable of managing the entire data pipeline, strategy, and finally, problem solving using effective tools and techniques to reach a desired accuracy level.

Data Scientist: A Data scientist is expected to leverage his vast knowledge of understanding algorithms and data types to solve complex business problems. These are data-driven decisions that take center stage in analyzing a problem and in pattern discovery. A Data Scientist must manage, analyze and strategise solutions using multiple statistical tools and techniques available to be leveraged.