SUMMER TRAINING

Course Description

Summer Training is a great opportunity that gives students practical, real-world experience in a working environment. Students are expected to complete their industrial training by spending at least thirty working days to gain practical experience. They will gain experience in a field of interest. Among the fields they can choose to study are web design and/or content management systems, project management, software development, cloud management, database management systems, embedded systems and business intelligence. At the end of this training, each student is obliged to submit a report of all the activities that took place in their summer training. In this report, students are asked to include what they learned, the mistakes they made, and the difficulties they encountered while participating in this training.

SUMMER TRAINING

Evaluation Tools (Active Term)

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Course outcomes

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Course Syllabus

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Reference Books & Course Materials

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Learning Outcomes

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Program Outcomes

1. P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
2. P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
3. P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
4. P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
5. P05 Utilize modern computing techniques to handle real-world problems characterized by massive amounts of data, such as parallel and distributed computing and machine learning.
6. P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
7. P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
8. P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
9. P09 Be able to effectively integrate data‐based solutions into the user environment and help non-technical professionals in exploring, visualizing, and using these solutions
10. P10 Understand their obligations under professional and ethical standards in relation to matters like data ownership and citation, data security and sensitivity and the privacy implications of data analysis.

Po-Lo Matrix

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