Program Educational Objectives (PEO):

The B.Sc. Data Science program describe accomplishments that graduates are expected to attain within five to seven years after graduation.

• PEO1 : Our graduates will excel with professional skills, fundamental knowledge, and advanced futuristic technologies to become Data Scientists, Data Analyst, AI Research Scientists, or Entrepreneurs
• PEO2 : Our graduates will establish their knowledge by adopting Data Science Technologies to solve complex real-world problems with accurate, thoughtful solutions
• PEO3 : Our graduates will engage in lifelong learning to excel in their profession with social and ethical awareness and responsibility

Program Outcomes (PO):

On successful completion of the B.Sc. DataScience

• PO1: Apply analytical and critical thinking to identify, formulate, analyze, and solve Complex real world problems in order to reachnuanced authenticated conclusions
• PO2: Possess the ability to demonstrate advanced independent critical enquiry, analysis and reflection of modern statistical methodology and computing
• PO3: Have a set of flexible and transferable skills for different types of employment, both within the Information Technology sector and beyond, in both global and local organizations
• PO4: Develop and implement data analysis strategies base on the oretical principles, ethical considerations, and deep, detailed and broad knowledge of the underlying data and its implications in the context from which the data was taken
• PO5: Be critical and creative thinkers, with an aptitude and appreciation for continue dself-directed learning in the evolving world of data science, artificial intelligence and social media
• PO6: Design and develop research-based solutions for complex problems with specified needs with appropriate ethical consideration for public health, safety, culture, society, and the environment.
• PO7: Establish the ability to listen, read, proficiently communicate and articulate nuanced data and information through traditional and digital channels to audiences with diver seperspectives
• PO8: Articulate and evaluate appropriate legal and ethical standard spertaining to all forms of communications, network security and human rights.
• PO9:  Showcase an understanding of the inter disciplinary nature of data, information and community and its influence innovation and progress within the current local or global context.
• PO10:  Be able to initiate and implement constructive change in their communities with their skills in data and information, including various professions and workplaces.

Program Specific Outcomes (PSO):

After the successfull completion of B.Sc. Data Science program the students are expected to

• PSO1: Ability to design, develop, implement and apply Analytical skills related to Research and Real-world problems
• PSO2: Ability to apply tools and techniques to provide successful solutions in the multi disciplinary field
• PSO3: Ability to critique the role of  information and analytics for a innovative career, research activities and consultancy/

Data Scientist: Data scientists are at the heart of extracting actionable insights from complex datasets. They use a combination of programming, statistical skills, and machine learning to analyze data and predict trends.

Data Analyst: Data analysts focus on processing and performing statistical analysis on existing datasets. Their work often involves creating visualizations, dashboards, and reports to help businesses make informed decisions.

Machine Learning Engineer: These professionals specialize in creating algorithms and predictive models to make predictions or automate decision-making based on data. They work closely with data scientists to implement and optimize machine learning projects.

Data Engineer: Data engineers build and maintain the architecture (like databases and large-scale processing systems) that allows for the efficient analysis and processing of large data sets. They ensure that data flows smoothly from source to database to analytics.

Business Intelligence Analyst: BI Analysts use data analytics and visualization tools to develop insights into the business performance and market trends. They help in strategic planning by providing data-based recommendations to the management.

Quantitative Analyst (Quant): In the finance sector, quants use data analytics to model and predict financial markets, helping companies in risk management, investment management, and trading strategies.

Data Analytics Consultant: These consultants work across industries, advising businesses on how to use data analytics to improve processes, increase efficiency, and boost profits. They often work on a project basis and may serve multiple clients.

Big Data Engineer/Architect: Big Data Engineers or Architects handle the management and organization of big data environments. Their work involves designing, building, and maintaining scalable and secure big data ecosystems.

AI Specialist: Specialists in artificial intelligence develop AI models and applications, often working closely with machine learning engineers and data scientists to integrate AI capabilities into various products and services.