BECOMING A DATA SCIENTIST AND ANALYST
As a student in tech, data science and analytics particularly, I felt the urge to grasp more of the technical skills of the theory I learned in school. I didn’t know how to go about this but joining the local tech communities on X, formerly Twitter, proved and continues to be of much help. One challenge that caught my eye was one dubbed the six-month challenge where one is urged to pick up a new skill they’d want to learn or upskill on and dedicate six months to learning the skill. As a student who was eager to grasp the technical skills of what I was learning in school, I decided to major in data analytical skills as a starting point and later on progress to data science related skills. I went ahead and picked a roadmap to follow on LinkedIn, one that I found suitable. Starting with Excel, moving on to SQL, Python, and finally Power BI.
Excel as a Starting Point
For Excel, YouTube was my mode of learning. I found a channel that offered what I needed in a simplified yet detailed manner. Here I was able to learn about entering data and navigating through a spreadsheet, creating formulas to solve problems as well as visualizing the data through charts and graphs. Onto more complex concepts, I was able to learn relative vs absolute referencing, importing and exporting text data or CSV files, the VLOOKUP as well as pivot tables. To put the above into practice, I was also able to tackle projects on payrolls, gradebooks, decision factors, sales databases, car inventories, and problem-solving templates. With this, I was able to move on to SQL.
SQL
For this, I learned from this website. I was able to learn the basics of what SQL does as well as the basics of relational database management systems. From there, I was able to learn the SQL commands and put them into practice. Some of the commands I learned and used include SELECT, FROM, WHERE, ORDER BY, JOINS, GROUPBY, and HAVING among many others. I also learned how to create and manipulate databases. For all the above I used MySQL as the preferred database.
Python
For Python, I partially used this website for the basics and a course on Udemy for the more advanced libraries. I am currently still on this but at a fairly good place having learned about the basic syntax, control flows, functions, data structures, file and error handling, objects, classes, inheritance, encapsulation, polymorphism, and some of the major libraries including numpy, pandas, matplotlib and seaborn. This is the most exciting part of my journey so far and I can’t wait to start doing and sharing projects as soon as I am done with mastering the basics of Python for data science.
I decided to share my progress since I believe in being an advocate of my work and challenging myself to do even more. From what I have come across so far, I have figured out that the internet is such a great place for studying and upskilling and more importantly, that God and the universe give you what you need if you ask and work for it. Can’t wait to share more on what I will be doing in the future.
To connect more, you can find me on LinkedIn via:
