SMGOIH
EAMCET CODE : SMED

B.Tech CSE (DS)

What is B.Tech CSE(DS)

Data Science basically is an amalgamation of mathematics, programming, statistics and design which are applied in order to successfully manage digital data collection. The main 3 components involved in data science are organizing, packaging and delivering data. Overall, it is a multidisciplinary blend of data inference, algorithm development and technology in order to solve analytically complex problems.

Scope

Being a Data Scientist is one of the hottest and trending career option of the decade. The demand for data scientists is huge, the number is said to be much higher than the available candidates. So, choosing data science as a career option has a lot of scope and will remain so in the near future.
A data scientist may be required to:

  • Perform research on the messy data available and frame questions that needs to be answered by his analysis on the data collected collect huge data from multiple sources.
  • Make use of high-end analytics programmes, machine learning and statistical methods to organise data into a predictive model
  • Clean the huge volume of data to discard irrelevant information
  • Explore and analyse the data to determine the trends, opportunities and also weaknesses
  • Produce data-driven solutions to conquer the most pressing challenges
  • Invent new algorithms to solve problems
  • Build new tools to speed work
  • Communicate the predictions from the data analysed through data visualizations and reports
  • Recommend effective changes for the existing strategies to companies
  • Career Opportunities

  • Business Intelligence (BI) Developer.
  • Data Architect.
  • Applications Architect.
  • Infrastructure Architect.
  • Enterprise Architect.
  • Data Scientist.
  • Data Analyst.
  • Data Engineer.
  • Programme Outcomes

    Engineering Graduates will be able to:
  • 1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  • 2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
  • 3. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
  • 4. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
  • 5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.
  • 6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
  • 7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
  • 8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • 9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • 10. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
  • 11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
  • 12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
  • Programme Specific Outcomes

  • 1. Understand, design and analyze computer programs in the areas related to Algorithms, System Software, Web design, big data, Artificial Intelligence, Machine Learning and Networking.
  • 2. Develop and implement computer science management policies and adequately protect an organization’s critical information and assets.
  • 3. Exhibit proficiency in analytics for providing solutions to real-world problems in Industry and Research establishments.