From July 13, 2020, I started my summer semester in MSBA program at UT-Austin. I’m thrilled to share how much I have learned from the courses. Because of the pandemic, we have completely remote classes, but learning experinces of mine are varied as I expected.
We have only two core courses in summer semester. As a typical Asia kid, I was still surprised by continuous assignments and projects. I would say these courses are pretty intense within a short time period yet pratical for giving initial knowledge of analysis.
Predictive Modeling
Programming language we use: R
Class size: 100+
For me, this class is kind of mathematical with many statistical concenpts behind each predictive models that we were using during classes. Though this class is very intense, it’s the one guided me to a new world of data analytics. Not only getting information from data, we want to do predictions with data in order to see how we can make our strategies more effective or successful.
We have learned regression models, KNN models, and decision trees etc. The point of using these models is knowing in what situations are they going to be the most applicable. In real world business, we as a data anaylst role not only getting information and insights from data, but also play an important role in decisions making process. Predictions are surly one of the critical methods.
For your information, there is one group project and one individual assignment in predictive modeling class. For the project, we were randomly assigned to groups, and our topic was conceived after first zoom dicussion. My group picked a car dataset eventually, since the data was clean already, nothing missing. we then divided into two small teams to figure out the best models to predict Miles Per Gallon of cars. I wasn’t familiar with anything at all as a begginer of predictive modeling at first, but that’s why I’m here to learn, to challenge myself.
Let’s wrap it up. If you are good at R language at first, that is definitely going to be an advantage for you learning this class. Professors (we have two half of classes, so two professors) went over the concepts but not the R code. I found TA very helpful, and Stack Overflow is always your best friends in any coding work.
Programming for Data Analytics
Programming language we use: Python
Class size: 100+
In the beginning of the class, professor Chakrabarti started with questions- why analytics, and why do we need to analyze data to assist comapanies making business decisions. Professor indicated that a business problem is differnet from a technical problem. In other words, we can’t just rely completely on technical skills. So we used analysis tools to dig into data along with our business knowledges. Our ultimate Goal as a data analyst, is to figure out impactful insights that increase benefit in companies.
We then installed Anacondo on our computers, and begin with basic syntax of Python, such as values, variables, and types. We also go over Control Flow (if-else statements) and functions. After a week of fundamental training in Python, we moved on to Dataframe and Series. To sharpen our skills of using dataframe, we have three group assignments and one quiz in which we have to use dataframe a lot to solve questions.
In the last week of this class, we processed form purely analyzing data to predicting outsomes with data. Since then, we focused more on building models of regression, classification, and clustering. Our classes then ended in a three-hours final exam.
To sum up, professor Chakrabarti have a fine sense of humour, so students enjoyed so much interating with him. In general, we advanced step by step through the whole course, and gained basic ability of using python as an analysis tool.
Conclusion
Though within pandemic, all professors and faculty were trying their best to give us a wonderful online learning experience as much as in person one. It was the beginning of my journey in US, and I’m looking forward to growing both my technical and business skills during these 10 months program with these amazing people.