2020 has definitely been an objectively crappy year... But in terms of programming experience, this year has been by far my most productive and enriching! It was my third year of coding, and second year of doing for work. I've learned a lot on the job and through self-study, developed my Python skills and even learned two new languages. Here's how my coding year progressed:
January
- Started a new job as a student in Data Science/Analytics at a digital funeral home (it's really more exciting than it sounds).
- Learned BigQuery on the job and improved my SQL skills.
- Started learning JavaScript for automating Google Sheets and creating custom DataStudio visualisations.
February
- Automated boring tasks at work with Python.
- Analysed the text and sentiment of business reviews with Python.
- Worked for the first time with speech-to-text for data analysis, using Python and Google Cloud.
March
- Created my first chatbot with NLTK.
- Built a simple FAQ chatbot with Rasa.
- Learned to create a chatbot with Dialogflow.
April
- Completed two DataCamp projects in R to refresh my knowledge.
- Enrolled in a uni course "Introduction to NLP with Python".
- Started doing coding challenged on codewars, LeetCode, and HackerRank.
May
- Created my data-related Instagram account @datalingo.
- Completed the Natural Language Processing course on Kaggle.
- Got my first coding challenges on Python and SQL for data-related job applications (and passed 2/3!).
June
- Started creating my Data Science portfolio on GitHub.
- Created several short programs for automating various tasks.
- Completed home assignments on Python and NLP for the uni course "NLP with Python".
July
- Used GitLab (instead of GitHub) for a team project.
- Completed a uni team project on sentiment analysis of German product reviews.
- Passed my uni course "NLP with Python"!
August
- Completed my uni-related psych-verbs project, about the classification of Romanian verbs of emotion.
- Learned Python for financial analysis.
- Learned MongoDB basics.
September
- Started a Data Science Bootcamp!
- Learned to implement algorithms and data structures in Python.
- Learned Julia for data analysis.
- Created an animated scatterplot of Gapminder data.
October
- Analysed and predicted the survival of Titanic passengers using ML classification models.
- Analysed and predicted the demand for bike shares based on weather data using regression models.
- Competed in two Kaggle challenges (Titanic and Capital Bikeshare).
- Built a bot that scrapes music lyrics and predicts the artist from input lyrics.
- Analysed and predicted the temperature in Berlin using ARIMA models and Prophet.
November
- Learned AWS (EC2 and RDS) and built a business dashboard with Metabase connected to a PostgreSQL database.
- Learned Docker and built a pipeline for streaming tweets, analysing their polarity, and posting them in a Slack channel.
check it out - Co-created a Markov Chain Monte Carlo simulation of customers in a supermarket.
- Learned Deep Learning and built my first neural network models for classifying images of clothes.
- Built a Neural Network model that generates text in the style of E.A. Poe poems.
- Created a Slackbot for student support with Rasa.
December
- Co-created a movie recommender system and improved my front-end skills (HTML, CSS, Flask) in the process.
- Created a program that detects emotions from speech and classifies live voice recordings, as my graduation project for the Data Science Bootcamp.
- Created a tldr; program that does sentiment analysis, named entity recognition, and summarization of web-scraped speeches from the German government, so you don't have to read it all.
- Started a mini-project of holiday-related programs that automate and liven up holiday wishes.
- Made my first open-source contribution to the codebase of SpaCy, by updating the Romanian stop words.
- Learned Java on Codecademy and Udemy over the holidays.
20201
Overall, it was a pretty codeful year! I did put a tremendous amount of work into developing my programming skills and spent many nights and weekends on learning and fixing bugs. But the feeling of satisfaction I get now looking back at what I accomplished makes it all worth it. For 2021, I have many ideas for exciting personal and work projects, so I quite look forward to the new year!