Data Science Course Evaluation and Improvement Report

This report provides a comprehensive review of a Data Science course, evaluating its curriculum, teaching methods, and practical components. The student discusses the course structure, highlighting the theoretical and technical aspects, including the use of Excel and the absence of practical labs for languages like R and Python. The report critiques the lack of engaging lectures, inadequate practical sessions, and the marking criteria. The student suggests improvements such as incorporating more practical exercises, increasing the emphasis on attendance, and integrating software like Hadoop. The author emphasizes the need for a more balanced approach between theory and practice, along with the inclusion of real-life examples and additional subjects like mathematics, statistics, and machine learning. The report concludes with recommendations for enhancing the course's effectiveness in preparing students for a career in data science.

Running head: DATA SCIENCE
Data Science
Name of the Student
Name of the University
Author note

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DATA SCIENCE
Data science is one of the new technologies that is going to hit the world in the next
generation of the computer science world. IT can be called an interdisciplinary field which
consist of the scientific methods, different processes and the algorithms systems. It can also
be called that it is the subject which included the studies related to the big data, the kind of
the data’s, data ware housing and other such subjects. This was the primary subject in the
syllabus, other than this there were two other subjects that were in the course of this semester
was the presentation techniques which included classes explaining the data visualisation and
the OLAP. The third subject was the technical part which would provide us the knowledge of
using the MS excel and for the understanding of the data visualisation including the Excel,
charts, graphs, pivot table and VBA. To be very specific tough out the entire session of the
semester there were no proper class that were given to us, nor the tutor provided any of the
video lectures that would have helped me to understand the subjects in a better way.
The practical part will provide the students with more and more knowledge and
practice of the languages that are made for the data science If there were been certain video
classes then it would be much helpful in understanding the topic. The lecturer just presented
us with the presentations slides and no other things, making the meaning of the subject bit
boring. Big can be explained as a subject in which there must be many of the practical classes
in the semester to understand the concept of the R language, python and other such languages
that are the founding stone of the of the big data concept. In this case, none of the practical
classes or the labs were held. IT produce the student to work with the real life scenarios and
explore real examples. Excel helps in the process of the summarising the data using the excel
tables and pivot tables and make them combine with the statistics part which helps in the
process of the visualisation This was one of the major problem for me to understand about the
subject. And as there were no practical class the subject of the technical aspect was not been
even touched. Being interested in the technical aspects much, I was very much disappointed

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with the same. Other than this, in addition there was a practical project which the student
would make something interesting and demonstrate what they have learned throughout the
semester, was not done. One more thing that was not right in the whole semester was the
marking criteria or the marks division of the subjects. The attendance is of the semester had a
total point of the 20% each. Attendance, Project, class exams, online quizzes, and writing
critique every week about the course However the same was not followed and the assignment
contained maximum of the marks which was a burden for me as even I have attended all the
classes my marks would become less if the assignment was not done properly. Although the
course was very much realistic, and helped me understand the basics of the data science
which included the understandment of the theory of the big data and data analytics which
would help me in the future projects and help in the completion of the practical part. Further
the course presentations were helpful for me to grasp the knowledge of the theory part.
There can be many of the changes that can be made in order to make the subject and
the classes more interesting and advanced. Data science is a subject which is more focussed
on the practical parts rather than the theory. Although the theory is one very much needed in
understanding the basic knowledge of the subject, but the classes should be more focussed on
the practical part. The practical part will provide the students with more and more knowledge
and practice of the languages that are made for the data science. The whole subject is focused
on the practical hence the practical is one of the must importance one. Also one of the other
major change can be made that the score for the percentage of the attendance can be
increased so that the students comes to collage every day. The use of the Excel is one of the
must thing that can be included in the course, this is because of the fact that the Excel is the
most used and most advanced software that can be used for the purpose of the data analysis.
IT produce the student to work with the real life scenarios and explore real examples. Excel
helps in the process of the summarising the data using the excel tables and pivot tables and

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make them combine with the statistics part which helps in the process of the visualisation.
Excel also helps the data scientists in the process of the sorting of the data in the order the
user wants. The conditional formatting is one of the other important feature of the Excel,
which helps the data scientists.
The making of the project can be made compulsory for the students so that the student
understand the use of the data science more vividly. The practical will also help the students
in discovering new pathways in the world of the data science. Providing video and inteeltual
tutorial can also be used so that the students like me understand the topic in an advance
manner. Providing the student with the real life examples can also help the student to
understand the objective in a better manner and also understand what kind of the researches
are going on in the provided sector.
The technical skills that are required for the subject are huge and only a small part of
the subjects are thought. Introduction of the subject’s like the Maths and statistics, machine
learning can help the student a lot in understanding the subject and the main objective of the
data science. Maths cannot be avoided in the field of the data science and is one of the most
useful one. Using the formula of the maths also helps in the use of the Excel study part. Other
than the excel software one of the other major software that can help the students to better
understand the big data is the introduction of the Hadoop. The software which is originally
developed the apache corporation is used for solving problems which involves massive
amount of the data calculation. The Hadoop also helps in the graph reduction techniques.
According to me if these type of the changes are made in the course the course will be
more understanding and the value of the source will also increase all the parts that are related
to the data science techniques. The combination of the subjects like the maths, statistics, big

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data and the software’s like the Hadoop and the Excel can help the student to more focus on
the practical part and make him one of the best data analytic in the world.