Concise overview of things learned. Break it up into Technical Area, Tools, Soft Skills
Technical Area: Although this past week I haven’t been able to attend any of the live meetings, I was able to grasp a general understanding of some of the functions used for data in R and Python. Additionally, I was able to learn new strategies for reading and analyzing scientific readings.
Tools: R programming language and Python
Soft Skills: I have been working on my problem solving skills since I needed to find a way on how to quickly get myself back on track with the project schedule.
Three achievement highlights
Understood how to properly read and analyze the scientific papers that will be used in the upcoming weeks.
Began connecting with others and expanding my network on LinkedIn
Learned and utilized programming languages to group together scientific data for analysis.
List of meetings/ training attended including social team events
I have been unable to attend any meetings or training due to finals and class time conflicts. However, I have been able to watch a few of the videos up until now and will be watching the other recordings in order to catch up.
Goals for the upcoming week
For the next week, my main goal will be to catch up and attend most, if not all, of the training and meetings. I will be re-organizing my schedule to keep me on track with my tasks. I hope to learn and practice more R and Python, and I wish to get to know my team and others this week.
Technical Area: During this past week (and the previous week), I was able to learn a variety of new functions for processing and exporting data. Some of these include affyQCReport and limma. Using these methods, I was able to analyze the imported data and look for any outliers within the data.
Tools: Asana, Slack, R, GitHub
Soft Skills: I have been communicating with my team and keeping them up to date with my progress and whenever I need help. Additionally, I have continued to expand my LinkedIn network.
Three achievement highlights
I was able to create and analyze various forms of graphs that were previously unknown to me.
I learned a variety of libraries that I could use to help make my data easier to read in addition to highlighting different trends.
I have learned more about gene filtering and how to use limma.
List of meetings/training attended including social team events
I have not been able to attend any of the trainings due to class conflicts, but I have been able to keep up with the powerpoints and documents provided in the google drive. Apart from that, I was able to attend a Python training session in week 3 that helped me get a better understanding of the programming language.
Next week:
I will be leaving after July 3rd, and will be spending the next week reviewing everything I have learned during this session.
Session Assessment
This session was a good experience for me. I was able to learn a lot of different techniques to analyze datasets, and learned a new programming language-- R-- and Object Oriented Programming for Python. My prior knowledge of Python was limited to the basics, but the intermediate training I attended in week 3 was very useful in teaching me more. I also learned how to use affyQCReport to generate a pdf of various visualizations that can be used to pick out the outliers and see the relationships between different arrays. The most recent week, I was able to get a general understanding of the importance of gene filtering through the use of limma(). From this, I was able to learn the usefulness of the Bioconductor documentations when I need help or don’t understand how to use a certain function. Additionally, I was able to connect with a lot of people on LinkedIn and was able to learn the importance networking.