My Datacamp + coursera Course Journal in 2023
After last time that I completed 16 courses in 2022 (Click)
I see it’s nice to still keep track of my course journey to rekindle my motivation… so here we gooo 2023!! 🔥🔥🔥
สารบัญ
Datacamp
[18 Jan, 7 Feb 2023] Course 1-2/2023 — Analyzing Data in Tableau, Calculations in Tableau
My job responsibility is back to Tableau again, and I need to customize the dashboard configuration thoroughly this time.
As DataCamp has Tableau skills track, why not take the course! 😎
Surprisingly, I recommend those who take Tableau course on this site to download the workbook and do the assignment on your local computer instead of using the remote session that the site provided because it totally slow. Causing you to complete the easy 5 min tasks by over 15 minutes…
Overall, the courses are well done since they touch the foundation of the tool.
I discovered many tricks that can fix my lengthy solution which I used to implement in the past.
[5 Apr 2023] Course 3/2023 — Introduction to ChatGPT
Learning this is a must I guess 😂😂 since it helps solving time-consuming tasks and leaves us do a better productive job. Though, it’s quite tough. Submitted incorrect answers many times! By the way, this course is about the theory and what’s behind the model i.e. Large Language Model (LLM) and gave you a brief of what the good prompt is. However, if you are looking for how to use ChatGPT in practice, I recommend you try the real tool by yourself rather than taking this course.
[27 Apr 2023] Course 4/2023 — Introduction to Data Quality
Such an underrated subject (only ~500 students enrolled) Essentially, the course inside is pretty knowledgeable and quite rare to find in other places. Here, it cramps the necessary parts in a single course. Not only it mentions Quality Check rule but also SLA (Service Level Agreement) and other principles needed to be aware of e.g. uniqueness, accuracy, timeliness. Recommended if you wanna explore this data subject.
[10 May 2023] Course 5/2023 — Dashboard Design Concepts
This is like a compilation of Dashboard Design Concepts from each essential books. A good starting course to understand the principle e.g. Type of dashboard – explanatory, exploratory, size, layout
[13 May 2023] Course 6/2023 — Forming Analytical Questions
Understand how to ask the right question with the real use case across industry e.g. Healthcare, Logistics, Retail. What’s the difference between Descriptive, Diagnostic, Predictive, Prescriptive kind of question.
coursera
Google Data Analytics Certificate
After my Datacamp subscription ends, and the right price hasn’t been there yet. Meanwhile, I received the scholarship from True SAMART Skill to learn certain specializations for free, hence I switch to study on coursera until the right DataCamp price comes.
[22 May 2023] Course 7/2023 — Foundations: Data, Data, Everywhere
Six steps of data analysis are
Ask
Prepare
Process
Analyze
Share
Act
This is not to be confused with Six data life cycle i.e. Plan, Capture, Manage, Analyze, Archive, and Destroy.
This coursera specialization walks us through each step. Foundations is the first course. It just describes the glimpse of each process. A good beginning for those who want see a big picture of Data Analysis.
[27 May 2023] Course 8/2023 — Ask Questions to Make Data-Driven Decisions
This sub-course digs deep to the Ask process. How to communicate across stakeholder and teammate. Ask effective question e.g. S.M.A.R.T principle (Specific, Measurable, Action-oriented, Relevant, Time-bound)
[5 Jun 2023] Course 9/2023 — Prepare Data for Exploration
The course emphasizes on Prepare phase. It discusses on data format i.e. Long vs Wide. Internal vs External. Continuous vs Discrete. Qualitative vs Quantitative. Nominal vs Ordinal, Structured vs Unstructured. What’s normalization, metadata, file naming convention. The best practice of prepare data so it retains the quality before doing the project and doesn’t give you a hassle later.
[15 Jun 2023] Course 10/2023 — Process Data from Dirty to Clean
Course about Analyze phase. It walks you through what to do when you have insufficient data to do the analysis. How to clean data with Spreadsheet or SQL. The basics of both tools are covered here. Why the documentation to transfer knowledge to other is useful and they effective way to craft your resume.
[28 Jun 23] Course 11/2023 — Analyze Data to Answer Questions
[8 July 23] Course 12/2023 — Share Data Through the Art of Visualization
The course teaches the theory of visualization and Tableau in practive. The toughest part is not how to use Tableau, but its theory instead e.g. What kind of objection when the stakeholders express concerns regarding the result compare to the previous result.
[17 Jul 23] Course 13/2023 — Data Analysis with R Programming
R syntax indeed is easy. Way more readable than Python. However, I rarely use R in my working days since I have to pick one language to be competent at first before moving on to another one HAHA, so I picked Python as I found Python is widely used in my environment. Nonetheless, once I feel comfortable enough in Python Pandas, I will comeback to master R!
[18 Jul 23] Course 14/2023 — Google Data Analytics Capstone
The last course to finish the specialization. The course contains an instruction to help crafting your portfolio. There are 2 Case Studiest that you can further explore to obtain your analysis result and put them in a resume. Anyhow, the case study is skippable. There is a question which asks you whether you skip the case study or not. Even though you skip the capstone, you can still go back to visit the material and complete the capstone.
Google Business Intelligence Certificate
[24 Jul 23] Course 15/2023 — Foundations of Business Intelligence
Let’s start a new track Google Business Intelligence Professional Certificate!
This track has 3 courses—
Foundations of Business Intelligence
Here the course walk you through the basic of BI. What’s the job title out there in BI scope. Differentiate BI and DA term (well, these two terms aren’t the same, yet, in the real world, the job description is kinda overlapped.) BI is more to deliver solution to the end-users e.g. the data, the dashboard whereas DA focused on data analysis and help strategizing a recommendation using data-driven approach. But at the end, we do both don’t we? teehee
This class helps you impose the requirement, documentation, define the impactful metrics.
[31 Jul 23] Course 16/2023 — The Path to Insights: Data Models and Pipelines
After documenting and gathering the requirements, now it’s the time to comprehend the idea of ETL, Data dictionary, Database schemas validation, Data Quality Testing, Data Model: Fact, Dimension table and why do we need them. Here, we get a glimpse to use BigQuery, Dataflow. Well, it’s Google tool!
[3 Aug 23] Course 17/2023 — Decisions, Decisions: Dashboards and Reports
Last course on BI track. It didn’t dig deep as much as Visualization course in DA specialization, but the idea explained overall is insightful and in a new perspective e.g. how to talk to stakeholder. Draft a mockup i.e. low-fidelity mockup. How to trade-off your dashboard feature when there are many audience use the dashboard.
In overall, BI track is a good extension track after you complete DA specialization. It covers how you should collect requirements with the stakeholders. Lean more on technical side of Data Model, Pipeline Implementation before visualize the result on Tableau (This section overlaps with DA track)
Google Advanced Data Analytics Certificate
[20 Aug 23] Course 18/2023 — Foundations of Data Science
A first course in Google Advanced Data Analytics Certificate. It is a brief summary and a rough overview of how Data Science career looks. It doesn’t dig deep into detail much yet. Of course, this is just an introduction for the upcoming courses.
[28 Aug 23] Course 19/2023 — Get Started with Python
Since basic DA track covers programming language such as R. This track focuses on Python. It covers the fundamental Python concept such as list, tuple dictionary, popular libraries which frequently use in Data Analytics job i.e. NumPy, Pandas. It’s nice to revisit this topic although it’s not new to me, hence I haven’t learned much from this course.
[7 Sep 23] Course 20/2023 — Go Beyond the Numbers: Translate Data into Insights
This course delves into EDA using Python, clean the data by numerous techniques e.g. String Manipulation, One hot encoding & label encoding. (well, these two encoding aren’t the same!) Find outlier and Visualize the end result through Tableau Public.
[19 Sep 23] Course 21/2023 — The Power of Statistics
Probably the course that I pay heed the most 😂😂😂 it walks through the overview of the Statistics. Such a good recap statistics course for those who studied them prior and already forgot lol (which is me!) Don’t expect them to go into detail thoroughly like the course you take on the university. Instead, deem at it as a course to brush up your rusty statistics knowledge.
[30 Sep 23] Course 22/2023 — Regression Analysis: Simplify Complex Data Relationships
Completed Regression Analysis course. phew ! just one more course to go in order to complete Advanced DA track. Hope I make it in time before my scholarship deadline ends 😂😂😂 TBH There are many new topics to learn in this course e.g. Logitic, Linear, logit (wat!?), Maximum Likelihood Estimation…A revisit is a must here
[9 Oct 23] Course 23/2023 — The Nuts & Bolts of Machine Learning
After I studied Statistics and Regression modules, now it’s time to mesh all the data in Machine Learning. Though, I learned ML so many times from other sites. Still, it takes some time to digest (and we need repetition to instill the ML foundation) With my difficulty that my real life job doesn’t involve with ML, so yeah if I need to grasp the idea more. I have to find a practical outside-job project in order to understand how concept works.
My final thought before the year ends
This was such a long haul of the study journey that I pushed myself a bit over the edge. I think it’s time for me to sit back, relax, revise and digest on what I have learned rather than keep learning new modules. Wanna prioritize the quality rather than the quantity here. It seems to me I studied too many but a few knowledge fills my head 😂
There are only two months left in 2023, and I think I’m pleased with what I was doing. and now it’s a high time for me to reflect and not being too hard on myself. Allocate my times to do other activities in other categories as well. Until thennn if you somehow stumble across my blog and read until this part, Happy Learning! 😀
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