Preparing for IAA: A Professional’s Journey 

I dedicated a year and a half to studying before enrolling in the IAA program. As a working professional without prior experience in data-related fields, I took rigorous online courses to acquire the necessary technical skills. Throughout this journey, I recorded several milestones in a journal, documenting my preparations for the IAA program.

My non-data background has never been an obstacle to joining the program. My persistent commitment to technical preparation has been the main drive behind this journey. 

Preparation Part 1 – Machine Learning (January 2022 – November 2022)

1. Online Data Science and Machine Learning Bootcamp (Jan. 2022 – March 2022).

I attended a three-month data science boot camp, where I delved into various supervised and unsupervised machine learning models. While overwhelmed by the complexity of the models, the boot camp allowed me to gain data literacy. It also marked the beginning of my data science journey, during which I set out plans to acquire coding and other technical skills. 

2. Machine Learning Specialization from Coursera (Oct. 2022 – Nov. 2022).

I learned various machine-learning algorithms and practiced homework in Python. I highly recommend this course, a classic for any data professional! 

Preparation Part 2 – Coding (March 2022 – August 2022)

1. SQL (March 2022 – April 2022)

I practiced SQL on LeeCode for two months. SQL is an essential tool for data analysts and scientists. Due to the practice, I felt prepared for the Fall I SQL classes and comfortable applying the tool to my practicum project.

2. Python (April 2022 – August 2022)

Many online Python courses cater to beginners, where you can grasp various data types, loops, and data manipulation skills. Learning Python is beneficial because it is a prevalent tool in the data science field. It also played a pivotal role for me to learn R, another programming language for statistical modeling.

Preparation Part 3 – prerequisites and preparation before the IAA program (January 2023 – June 2023)

As a full-time working professional, it took me half a year to complete the following courses before the IAA program. These prerequisites were instrumental in preparing me to start the program. 

  1. Took Introduction to Analytics 2, an online self-paced statistics course by Dr. Aric LaBarr (January 2023 – March 2023).
  2. Learned R coding from Data Camp, which is an online platform for learning programming language (April 2023).
  3. Practiced Python through an online course (April 2023 – May 2023).
  4. Statistics primer course offered by the IAA (May 2023 – June 2023).

During my preparation journey, I also took a month off and seized the opportunity to reconnect with friends and engage in self-reflection. The introspection helped me to assess whether I was on the right path and solidified my decision to pursue the IAA program. 

After joining the program, I am surrounded by talented classmates with previous statistics and coding experience.

A group of people sitting at a table

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Instead of comparing myself, I have actively seized the opportunity to learn from them. It’s remarkable how frequently I have gained new coding tips or deepened my understanding of new concepts through post-class discussions. Lastly, my non-data background has never been an obstacle to joining the program. My persistent commitment to technical preparation has been the main drive behind this journey. 

Columnist: Lu Shen