I have been quietly excited for this post the entire series because it is the one I am most confident in. This one feels like a mammoth of information that I didn’t know I had.
There are resources everywhere. Even more, resources that are free and low cost. I’m talking, Youtube, Google Certificates, organizations you can join, websites you can visit. That’s for everything, not just learning. It’s project ideas and helpful information to get your brain going when you’re stuck on something. It’s portfolio ideas. Ways to help make your presentations flawless. Everything.
I’m going to take a moment to say that getting an education at an accredited university is definitely a good way to go if that’s what you want to do, you have the means and the time for it. Depending on what kind of focus you want your data career to have, you have your pick of degree choices from economics, stats, computer science, math, biology…
Understand too that if you already have that educational background, you can probably use it for something, even if it isn’t science or math focused in any way. Companies usually prioritize people who have an education, as a Bachelor’s degree is the level of education that’s typically asked for.
Degrees are an incredible foundation, and a great way to find domain knowledge. An economics or math major might find a good niche in financial analysis or business analysis, and a biology major could find work in analysis as an epidemiologist. The possibilities feel pretty endless sometimes.
Domain knowledge and building a foundation with degrees are one thing, but you’ll also need to have a decent understanding of the tools used for the specific path you’re taking. Whether that’s basic analysis, visualization, or it goes into modeling and working with AI, or natural language processing.
The following programs and certifications will help you understand those tools you’ll be expected to use most frequently. They’ll also teach you concepts within working with data (A/B testing, what makes a good survey and how to get insights, data literacy), and very basic problem solving methods.
Data Specific Certifications & Programs
Google Data Analytics Certificate –
Hosted by Coursera, a great resource to get started. They cite about 6 months for completion with 10 hours a week.
Coursera is always having sales, so never buy a course full price. At the time of posting this, it’s free.
This certification is 8 courses all told, and looks to cover spreadsheets, data ethics, SQL, sample size determination, problem solving, metadata, and questioning, among others.
I have heard a lot of good about this certification, and while I haven’t done it myself yet, it comes highly recommended in the circles I’m in, so don’t sleep on it, especially if it’s free!
Related: There is also a certification exam for a Google Cloud Data Engineer.
This will take you to a search page for exams and self-paced learning courses to get certified in certain areas, with specific tools, etc. PowerBI, specific SQL versions, Azure Data Scientist Associate… There really is a lot here to choose from, and with it being from a trusted source– Microsoft– you know you’re getting quality.
Just a note that some of the programs and more frequently for the exams, there is a cost attached. The learning is free, but the exam will be around the 1-200 dollar range.
I promise I’m not being paid by WiD for all of these entries talking about them! But I would definitely be doing a disservice by not being honest about how much I’ve gotten out of this organization. It’s really helped me define my path and get working knowledge and experience.
You can read about my experience with the Machine Learning Portfolio Builder program they have, and the Residency Program that I was chosen to be part of.
There are still more benefits of having a membership, and one of them is easily the amount of networking that can be done. There are virtual events, and the people you meet in the programs are usually like-minded individuals with the determination to break into data.
Other than those programs, there’s the Slack channel you’ll have access to, the mentorship program (whether to be a mentor or mentee) and free access to Datacamp either in a group learning setting or at your own pace.
The membership for this is just 120/yr. For the value I’ve gotten out of it myself, I found it incredibly fair. Scholarships also exist if the cost is not possible for you!
Datacamp (with or without Women in Data membership)-
I admit that I haven’t done this one yet, but I’ve heard a lot about it. Like I said in the WiD section, you can do this with a group of people across, I believe, 8 weeks, with the learning pathways. There is a selection of courses to take, 5, that will qualify you for the data analysis certificate, and another selection of courses (the same as data analysis with one switched out) to qualify you for the data science one.
This one reminds me of Codecademy, but focused solely on data, with the ability to choose a course for a career track, or to learn specific languages or tech stacks (stacks refer to more than one programming language, used together).
I believe they often have discounts on membership, and it’s yearly access. $300 at full price for one person, which is currently, as I type this, discounted by half at 150. For teams it’s the same price but per person, so for a team of two it would be 300.
The only reason I know about this is from a good book that helped me get up on my data feet: Confident Data Skills. The Data Science A-Z course was free with the code that’s in one of the first pages of the book, and I found it at the library.
For a pure beginner, this was an incredible book and course. It helped me with jargon and helped me understand what I would be doing in a career in data. It also helped me break gently into an understanding of more advanced statistics and data science (ie: modeling).
The Data Science A-Z course was also my introduction to Tableau, which I promptly fell in love with.
Remember this course is free with the code at the beginning of the book (available from the sample). Or you can see if your local library has it!
Outside of that, Super Data Science and all of its courses are available for $35/mo or $276/yr. I believe there are sales a couple times a year or so for about half off the yearly price.
Youtube: Alex the Analyst (and other honorable mentions) –
Okay, this one is a little different than the other things in this list. I’ll be honest that I didn’t know about this channel until recently, but it’s already had a big impact on me.
Alex’s videos are beautifully organized by tool, and includes tutorials for Excel, PowerBI, and SQL from beginner to intermediate. There are also videos for projects that he has, as well as resume advice. This feels like a lot more substance and value in a basic YouTube channel than I’m used to seeing.
Since this entry was technically for YouTube, I did want to mention that there are other channels that do something similar. Simplilearn‘s data analysis playlist plus their entire programming catalog. Edureka for their data analysis playlist and programming catalog as well, Corey Schafer for Python videos, especially libraries like Pandas, Matplotlib and Numpy. I’d be lying if I said Corey Schafer didn’t help me through some of the harder programming basics with Python (OOP still gives me some issues.)
General or Comp Sci Focused Catalogs with Data Options
Codecademy – I have used Codecademy off and on for my data journey for a while. I’m not sure the format really jives with me personally, but I wanted to let you know it’s a possibility.
They have individual languages, and they have career paths, just like Datacamp.
The other thing I’m a little dubious about is that they are always changing things. It’s good that there are always updates, but I was in the middle of my Data Science: Analysis career path and it entirely changed up on me. I was learning lists in Python, and then suddenly I was working in SQL because of everything restructuring.
They do tend to let you know when there’s going to be a change, but it wasn’t much time.
Still, they’ll hold your hand through the beginning and slowly teach you the concept of problem solving on your own. For a lot of the courses, they’re starting from scratch, with someone they assume is a total beginner. You can jump around for a refresh on certain concepts/programming methods, or you can just go from start to finish naturally.
The career paths also give you projects you can add to your portfolio.
Unless you catch it on a sale, this one is $40/mo.
Coursera – Coursera has a wide, varied catalog of just about anything you could possibly want. They have degrees, certifications, there’s university use and professional/”enterprise” use for it. There’s a lot here. Interested in Social Work? It’s here. Interested in Database admin? It’s also here.
Alex the Analyst has videos on coursera learning, and one where he goes through to show that there are guided projects, as well as just projects.
Cost varies depending on what you’re into, but you pay based on individual course, and can join for free. The Google Data Analytics course looks to be totally free and accessible for free members.
Harvard’s CS50 – For people with intermediate/advanced programming knowledge. This course is difficult but it’s been lauded as one of the best for computer science and programming knowledge and tends to look nice on resumes as well.
LinkedIn Learning Courses – Requires Premium – I believe this is fairly new, that LinkedIn recently created a full on catalog of learning materials which is perfect for people who are transitioning into new roles. I know they have an SQL course that focuses on using SQLite3 and SQLite studio. It stands to reason they’ll have other courses on different BI Tools and languages as well.
LinkedIn Premium is $40/mo unless you get a discount code.
Websites to Challenge or Refresh Yourself
W3Schools – This one was probably the most helpful to me for learning and refreshing myself on SQL. It has lessons for most, if not all, languages. For SQL, they’ve broken things down clearly and you can choose where you want to go within the lesson, if you need help on the more intermediate queries, joins, whatever it is you’re looking for.
I really love this option because of its accessibility and I’ve gone back to it time and again. It’s a tried and true resource for me.
I was under the impression it was fully free, but it looks like it has a pro version and a free version. Fortunately this one is one of the cheaper options at 4.99/mo. And as I’m writing this I am finding out that W3Schools has a certifications page. The cost of which is all laid out on the catalog as you search through, very convenient.
SQL Murder Mystery – I have not tried this one yet, but it’s supposed to be a cute little SQL game that will help you consider queries in unique ways. I try to recommend it everywhere because I love the concept, even if I haven’t gotten a chance to sit and go through it myself.
Mode – This is a website that’s focused on SQL. I was using it for a refresher about a month ago and it was decent, it has that sense of leading you by the hand slowly until it lets you figure things out mostly on your own. It reminds me a lot of Codecademy in that way.
Unlike W3Schools, this one doesn’t let you jump around as much, so you have to start at the beginning and get to where you want to go from there.
If you’re into a more interactive experience, this one will be for you. I believe it’s a free month trial and then there are professional/individual options for a membership.
HackerRank – I am adding this with a disclaimer: this is typically used to help overall programming knowledge in relation to technical interviews for positions with a tech stack of some kind. As far as I recall, it’s similar to LeetCode in that it constantly throws challenges at you.
You’re a lot more likely to encounter technical interviews when you’re applying for roles in Data Engineering or Data Science, because they tend to require a certain level of understanding of programming knowledge and languages.
That said, even if you aren’t looking into a more technical role in the Data Engineering space, I still find this useful.
Documentation for Data Focused/BI Tools
Below are white papers/user manuals/help guides/official documentation for each of the tools listed. Hover over them for the link.
This one got long, but I hope that it’ll help having all of this at your fingertips like this.
A note about certifications and adding certain classes to your resume: I’m still figuring out what to share and what not to on my resume, so I’d just use your own discretion. A portfolio would be better to show you know what you’re doing with what you’ve learned so far, and we’ll get into that in the next post.
There are, of course, so many things that I didn’t post here. There’s webinars and hour long panels with data professionals that give you insight into the industry, there’s using Stack Overflow for the errors you encounter while coding, and using Google to figure out the answer to a question.
There’s so many posts on LinkedIn, there’s communities on Discord and Slack that will help and will get you connected with people who can help you when you’re stuck on a problem. There’s reddit.com where you can look for specific forums, called subreddits, for like minded people with some of the same issues.
This post is a lot but trust me when I say there’s stuff I didn’t or couldn’t cover. I’m going to try to add more, whatever I don’t get to, in a wrap up post.
Like I said, the next post will be about putting together a portfolio, and I’m expecting it to be the final post in the series.
I hope I’ll see you in the next one, and until then, happy learning!
Kat's Data Wonderland 
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