Data Analyst Starter Pack: Skills and Projects to Get Hired
Statistician turned Data Scientist with a Psychology background. I create clear, practical content that makes statistics easy to understand.
Shortcut Link to “Becoming a Data Analyst” Course
Note: this post is part of a series of posts about Breaking into Data with a Non Technical Degree
To convince someone to hire you for a data role, you must first show that you have the skills to do the role. For those who are transitioning into the field of data — whether you are a fresh graduate or a mid-career switcher — I’ve curated a course to teach you about all the essential skills you will need for your Data role.
Whatever you see in my course — write them on your resume. Be prepared to be questioned about your knowledge of these things during your interviews. Build projects using all the things I teach. With all these in place, it will be a lot easier to convince employers that you are suitable for the role.
Now, because the data field is so broad — I will be focusing on the most entry level of data roles—the role of a Data Analyst.
How to become a Data Analyst
The role of a Data Analyst involves you using a variety of tools to analyse, visualise, and explain the insights from a Dataset. It is important to be comfortable with using different tools — because you don’t know which software your company will favour at the end of the day.
The most common ones are: (1) Excel, (2) PowerBI, (3) Tableau, and (4) Python. And my course teaches you exactly that.
P.S. Unlike other courses, I will be using all the free versions of these for my course — so you can follow along with me without any additional cost!
Softwares, however, are merely means to an end. Regardless of which software you choose — the principles of data aggregation, data cleaning, and data reporting remain the same. Averages are still averages, whether you compute them in Excel or Python!
As a result — I’ve organised this course in an interesting manner (to me at least, and hopefully to you too!) I will be using the same dataset for the ENTIRE course — and you will be learning about how to obtain the SAME set of results via different means in my course.
The questions are as follows:
How many tenants do you have in total?
Which is the tenant with the highest total profits?
Which is the tenant with the lowest total profits?
Plot a graph to showcase which tenant has the highest daily average footfall
What is the total amount of profits all your tenants made as a whole?
How much revenue did the Beauty & Fashion category of tenants make as a whole?
Make a chart to showcase how average cost per item varies by category
The rationale for doing this is simple: (1) I want to drill into you the more common computations that you will be required to do as a data analyst — and what better way to do that than repetition? (2) Being able to use different means to get to the same results allows you to cross check your reports in the future.
You will soon begin to realise that each method has an area in which it is best — which is why some people eventually settle for one software over the other. But at this entry level — these differences will not yet be too perceptible to you (aka these computations are the most basic ones — you should be able to do them no matter what software is given to you)
Course Outline
Briefly, here is what you can expect to learn in my course.
Excel
COUNTA(), SUM()
Sorting in Excel
Graph Plotting in Excel
Pivot Tables
PowerBI
Using PowerBI for Dashboarding
Averaging, Summing, Counting in PowerBI
Bar Charts
Data Aggregation in PowerBI
Tableau
From Sheets, to Dashboards, to Stories
Bar Charts
Highlight Table
TreeMap
Python
Basic Introduction to Programming
Using Pandas Library for Data Manipulation
Using Matplotlib Library for Data Visualisation
Pre-Employment Technical Test for Data Analysts
Simulates real hiring tests used by top companies to assess data analyst candidates
30 carefully created questions spanning multiple domains: (1) analytical thinking, (2) software competency, (3) data manipulation, (4) business interpretation
Mix of theory and applied scenarios to mirror real workplace challenges
Detailed explanations for every answer — so you learn while you practice
My course is organised in a bite-sized fashion — it has many lectures, but each lecture focuses on one core skill and is rather short (usually about 5 minutes). I chose this teaching philosophy to respect that fact that we are all time-starved in our lives, and often do not have the time to sit down for 2–3 hours straight to learn something. Hope this style of teaching would be better for my audience!
Why My Course Over Others?
The internet is full of data courses — but here’s what makes mine different:
Practical. No fluff. Just pure, useful skills.
You’ll work with real datasets and real business problems, so you won’t just learn theory — you’ll solve problems that mimic what employers expect you to handle on the job. The lessons are bite-sized (around 5 minutes each), perfect for busy learners who want to learn at their own pace without sitting through overwhelming lectures.
Additionally — don’t worry about expensive software! This course is designed around free versions of Excel, PowerBI, Tableau, and Python, so you can follow along without paying a cent! Download instructions are provided in the course as well 😉
By the end, you won’t just know about data analysis — you’ll be able to do it confidently.
Ready to land your first data role?
This course gives you the core skills, real projects, and practice tests you need to convince employers you’re job-ready. Stop guessing what to learn — start building a portfolio that gets you hired.
👉 [Enroll now and start your Data Analyst journey today]
Side note 1: Want exclusive discount codes to my courses? Subscribe to my Telegram Channel over here!
Side note 2: I priced this at 44.99 USD. Udemy auto-converts the price to your home currency during payment, so the price may flucuate from time to time.
Side note 3: If you’re planning to purchase, I’d really appreciate it if you used my referral links (attached in this post). I receive a significantly higher percentage through it, and it directly supports the work I do.