How I Levelled Up My Data Science Skills In 8 Months. For this post, I am going to share the 3 things I did during my furlough period to ensure that I move closer to my goal.
March 2020, I received a call informing me that I would be furloughed until further notice — informally meaning I’d be paid to learn. I knew the probability of me being made redundant after the furlough period ended was high since there were no projects I was actively working on.
Even though I hadn’t been doing much work with data at work, the thought of not being able to do any meaningful work with data bothered me. Nonetheless, I felt like my options regarding what I could possibly do next were limited since I did not get much practical experience at work. Don’t misunderstand me, I had been doing work as an intern, but I hadn’t done anything to significantly (or even marginally) improve the business (at least in my eyes) in my time. I was in a very low place, lacking self-belief, doubting my skills… For me, the furlough couldn’t come sooner.
The first transformative decision I made was to commit to becoming a future-proof indespensible Data Scientist.
When you make a commitment to do something, a force from within drives you. I wake up every day thinking I must be better today than I was yesterday and that is what drives me. However, for this post, I am going to share the 3 things I did during my furlough period to ensure that I move closer to my goal.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics.
Simple explanations of Artificial Intelligence, Machine Learning, and Deep Learning and how they’re all different
Artificial Intelligence (AI) will and is currently taking over an important role in our lives — not necessarily through intelligent robots.
Data Augmentation is a technique in Deep Learning which helps in adding value to our base dataset by adding the gathered information from various sources to improve the quality of data of an organisation.