B.Sc Data Science and Analytics

Program Educational Objectives (PEO):

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

• PEO1: Develop in depth understanding of the key technologies in data science and business analytics: data mining, machine learning, visualization techniques, predictive modeling, and statistics
• PEO2: Apply principles of Data Science to the analysis of business problem
• PEO3: Demonstrate knowledge of statistical data analysis techniques utilized in business decision making

Program Outcomes (PO):

On successful completion oft he B.Sc. Computer Science with Data Analytics

• PO1: Exhibit good domain knowledge and completes the assigned responsibilities Effectively and efficiently in par with the expected quality standards.
• PO2: Apply analytical and critical thinking to identify, formulate, analyze, and solve complex problems inorder to reach authenticated conclusions
• PO3:  Design and develop research based solutions for complex problems with specified needs through a ppropriate consideration for the public health, safety, cultural, societal,
  And environmental concerns.
• PO4:  Establish the ability to Listen, read, proficiently communicate and articulate Complexide as with respect to the needs and abilities of diverse audiences
• PO5:  Deliver innovative ideas to instigate new business ventures and possess the qualities of a good entrepreneur
• PO6: Acquire the qualities of a good leader and engage in efficient decision making.
• PO7: Graduates will be able to undertake any responsibility as an individual / member of multidisciplinary teams and have an understanding of team leadership
• PO8: Functionas socially responsible individual with ethical values and accountable to ethically validate any actions or decisions before proceeding and actively contribute to the societal concerns.
• PO9:  Identify and address own educational need sinachanging world in ways sufficient to maintain the competence and to allow them to contribute to the advancement of knowledge
• PO10:  Demonstrate knowledge and understanding of management principles and apply these to one own work tomanage projects and in multi disciplinary environment

Program Specific Outcomes (PSO):

After the successful completion of B.Sc. Computer Science with Data Analytics program the students are expected to

• PSO1: Impart education with domain knowledge effectively and efficiently in par with the expected quality standards for Data analyst professional
• PSO2: Ability to apply the mathematical, technical and critical thinking skills in the discipline of Data analytics to find solutions for complex problems.
• PSO3: Ability to engage in life-long learning and adopt fast changing technology to prepare for professional development.
• PSO4: Expose the students to key technologies in data science and business analytics:data mining, machine learning, visualization techniques, predictive modeling, and statistics.
• PSO5:  Inculcate effective communication skills combined with professional & ethical attitude.

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.