Programming and Big Data Analysis 7,5 Credits
Course ContentsThis course develops the students’ ability to manage big data and to analyze it using descriptive and graphical methods. Big data refers to data that is so massive in data volume, so rapidly changing and growing in volume, or so complex and unstructured that it is challenging or impossible to handle by employing conventional techniques and software. The course will contain three major parts described below.
1. A Practical and modern introduction to Python:
This part will introduce Python which is a powerful high-level multipurpose programming language. We cover fundamental programming concepts where students learn how to develop their own code but also to use libraries and packages for management, descriptive analysis, and visualization of big data. The students will learn basic parts of the Python language, how to use Python for scientific computation with matrix algebra, and how to make use of packages and libraries in Python to efficiently solve a variety of problems.
2. SQL (Structured Query Language)
The second part of the course SQL is introduced. This is a specific programming language created for accessing, retrieving, and manipulating data in databases and data warehouses. In this part of the course, students will learn the most important aspects of SQL language. In the end of the course, students will have practical skills in querying and managing data using SQL.
3. Integration of Python and SQL
In the final part we integrate Python with SQL. When analyzing big data, it is important to know how to exchange data and analytical results between different programs. The students will learn how to retrieve, manage, and analyze data using SQL and Python.
Connection to Research and Practice
This course provides the students basic software skills that are useful for manipulating and working with economic and business data, with a special focus on “big data”. Such skills are important for researchers to identify business and economic trends as they are happening and to uncover relationships in between variables in business and economics that would otherwise be hidden due to the limitations of traditional methodologies in dealing with big data. The ability to work with big data is a valuable skill for making business decisions and economic policy decisions.
PrerequisitesThe applicants must hold the minimum of a bachelors's degree in Business Aministration or Economics equal to 180 credits including 15 credits in Mathematics/Statistics/Econometrics
Level of Education: Master
Course code/Ladok code: JPBR22
The course is conducted at: Jönköping International Business School
Previous and ongoing course occasions
Type of courseProgram
SemesterAutumn 2023: Aug 21 - Oct 29
Rate of Study50%
Course coordinatorZangin Zeebari
Tuition fees do NOT apply for EU/EEA citizens or exchange students15000kr