The entire course is divided into 4 sections.
- Python Preliminaries
- Fundamentals of Python
- Fundamentals of Data Analysis in Astronomy
- Final Project
More details about each section and the learning outcomes from each can be found below.
The course involves learning and mastering python as well as learning some fundamentals of astronomy and machine learning. The course is designed for a duration of 12 weeks (3 months) spread out over a 24 week (6 month) period.
Students will start by learning the basics of python. And then move on to learn about public data sets in astronomy and the tools required for data analysis. Students have a choice to explore problems using image data or time-series data. Depending on their choice they may need to learn more advanced libraries in python. Students that have successfully completed these investigations can opt to do a machine-learning project.
Find the complete syllabus for the course here.
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Python preliminary
- Mostly instruction and hands-on
- Course objectives:
- Understand how computers read source code and perform an action
- Learn to write algorithms and flow chart for any given programming task
- Describe the different ways of writing code - scripts, REPLs and IDEs
- Be able to install and use jupyter-notebook or google colab
- Understand the importance of packages or modules in python and be able to explain what happens when code is imported
- Be able to install and use external packages in python that are not part of the standard library
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Learn the fundamentals of python programming
- A mixture of online materials and self learning through problem solving
- Course objectives:
- Understand the basic concepts of programming
- Get familiar with the python syntax
- Solve problems in 10 different areas ( in the python exercism track)
- In order to pass this course students need to do at least one problem each from at least 6 out of the 10 areas. They should also give an offline presentation based on what they have learnt in this course and the previous course. Optionally they will also be required to pass an offline exam.
- After passing this exam the students might be eligible for a certificate in the basics of python.
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Learn the fundamentals of data analysis in astronomy
- A mixture of online materials and self learning through practical assignments.
- This module consists of two sub courses: observation astronomy and astronomical data analysis
- Course objectives (observational astronomy):
- Understand how astronomical objects are located using RA and DEC
- Understand how the magnitude system is used to measure the brightness of objects
- Be able to explain what the modified julian date represents (MJD)
- Be able to explain why different kinds of wavelengths are used for observations in astronomy
- Be able to explain the working of an optical telescope in astronomy.
- Course objectives (astronomical data analysis):
- Learn about star catalogs and modern sky surveys
- Understand the different online tools available for astronomical investigations like VIzier, Simbad, Aladin, Topcat etc.
- Understand the need for using databases and the casjobs interface
- Know the different packages in python that are designed for astronomy and their purposes.
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Final Project
- The last module involves the application of concepts learnt in the previous three modules. Hence this can only be started if three previous modules have been completed. This includes the final project. Here we have a choice based path. Two choices are available now - Variable star track and Galaxy track.
- This part of the course should start not later than 4 months into the start of the course.
- After selecting a particular track, students are required to start preparing a project report. A template for this project report can be found here.
- The draft of the project should be shared through google docs or overleaf. The final project report (with proper figure placement, allignment, citations etc.) can be written preferrably in LaTeX using overleaf or any WYSIWYG (e.g., Microsoft Word, LibreOffice Writer, Google Docs) word processing software.