FAQ BDA

QUESTION1

Why should one pursue B.Sc. (Hons.) Data Analytics and Artificial Intelligence?

ANSWER1

This programme aims at providing the students a thorough understanding of data analytics and AI by gaining awareness about data related activities: Capture, Maintain, Process, Analyse and Communicate.

It develops necessary skills to future proof their employability. They will develop cross-disciplinary skills in the fields of statistics, mathematics and computer science to become data scientists, data engineers, analysts, and can make careers in healthcare, business, retail, social networking companies, etc.

QUESTION2 

Is Maths Compulsory for doing B.Sc. (Hons.) Data Analytics and Artificial Intelligence?

ANSWER2

No, this course can be opted by a XII pass student from any stream: Science, Arts or Commerce. Necessary Maths and Statistics papers will be taught in the three year duration of this progamme.

QUESTION3

What are the highlights of  B.Sc. (Hons.) Data Analytics and Artificial Intelligence program at IISU?

ANSWER3

This programme is best to opt due to following reasons:

  • No technical background required: It is not necessary for the student to have a prior knowledge of maths or any other discipline.
  • Curriculum Development: Curriculum is developed in  consultation  with Industry experts and academicians in the related domain.
  • Focus on developing cutting-edge skills in progressive manner: The curriculum focuses on continuous learning of the students and delivers statistical, mathematical and AI concepts along with sound knowledge in a number of software including Python, R, Tableau, PowerBI, SQL and Hadoop.
  • Industry exposure through internships and capstone projects: The curriculum focuses on experiential learning of the students through case studies, hands-on training on essential technologies, internships, capstone projects and  expert lectures.
  • Growing Employability Opportunities: This programme has been started because of the growing career opportunities in the field of data analytics and artificial intelligence. The demand for data analysts is rising as the organisations are facing challenges to handle bulk data and derive meaningful patterns for their benefit.
QUESTION4

What is the pedagogy adopted to train the students?

ANSWER4

The course focuses on holistic development of a student by inculcating technical as well as transferable skills. The pedagogy involves:

  • Project-based learning
  • Peer teaching and learning
  • Industry exposure & hands-on trainings
QUESTION5

What approach do you have for placement of the students pursuing courses from your institute?

ANSWER5

The University has a full-fledged Training Placement & Counseling Cell which looks into the overall planning and execution of career guidance, career counselling, and employment opportunities for the students.

QUESTION6

What are the career options after pursuing B.Sc. (Hons.) Data Analytics and Artificial Intelligence?

ANSWER6

This is a three-year degree programme. After completion of the degree, the students can choose amongst higher studies, jobs or start their own venture.They can go for jobs such as Junior Data Analyst, Data Annotator,  Business Analyst , Data Quality Analyst, Business Intelligence Analyst, Analytics Manager , Data Visualizer, Data Engineer, Data Scientist, Web & Social Media Analyst, Process Analyst

Hence, B.Sc. Hons. Data Analytics and AI is a degree with ample career opportunities in diverse industries namely healthcare, Banking, Financial Services, and Insurance, retail, social networking companies, biotechnology, Media & Entertainment, telecommunications, digital marketing  to name a few.

QUESTION7

What are the career options after pursuing B.Sc. (Hons.) Data Analytics and Artificial Intelligence?

ANSWER7

The syllabus can be accessed through following link

https://csit.iisuniv.ac.in/courses/course-detail/BSC(H)-Data-Analytics-&-Artificial-Intelligence

The papers covered are:

  • Data Visualization
  • MATLAB
  • R
  • Python
  • SQL and NOSQL
  • Machine Leaning
  • Linear algebra and calculus
  • Deep Learning