springboard data analytics review

Springboard Data Analytics Review: Is it worth in 2021

If you are in the process of deciding which data analytics course to take, then this blog post is for you. I recently completed a springboard data analytics and here I am sharing my springboard data analytics review. Have some insights about what it’s like to complete the course.

Rating: 4 out of 5.

I had a college degree, but I was currently working in a factory. I hated my job, and it was going nowhere.

I was looking for a technology-based program that would get my foot in the door at some tech job that would actually be a career.

At the time I shopped around for a program that was roughly 6 months and not relatively too expensive (at the time), and I think I chose Springboard for its job search resources.

Right now I am searching for a job, but it has only been one month.

Here I am sharing my journey in the Springboard Data Analytics program to give you insights into how I prepared and successfully completed it.

Why should you choose springboard for data analytics?

The Springboard Data Analytics Course is one of the most popular courses on the Internet. It’s easy to see why it’s so popular. With its interactive lectures, job guarantee, and engaging content, Springboard ensures that you’ll be engaged for hours on end.

The Springboard team has put together an excellent course that provides real-world examples of data analytics in action – from how to calculate ROI, to customer segmentation analysis.

Springboard also offers a lifetime access pass which means you can come back at any time!

If you’re looking for a new career or just want some extra skills in your arsenal then I would highly recommend checking out the Springboard Data Analytics course.

Also Read: Udacity data analyst review

Syllabus of Springboard Data Analytics

Springboard Data Analytics program will help you learn how to use the power of big data to solve real-world problems. In this Springboard Data Analytics program syllabus, the Course cover:

1. Framing structured thinking

The structures used HDEIP and SMART frameworks, which are ways of framing problems. 

These seemed obvious to me, and I don’t know if they are used specifically in the business place or worth learning. 

We practiced writing some statements and following these frameworks in business scenarios. 

2. Analyzing business problems

I’m assuming this is referring to the Excel unit.  This was done mainly through tutorial videos and a project. 

With the importance of Excel to data analysis, I thought there should be more practice and more in-depth coverage of Excel. 

While the project reviewed common Excel skills, it definitely didn’t prepare me for a career using it.  Having taken a Coursera Excel course, I felt they left a lot out. 

3. Connecting data using SQL

Most of the teaching of SQL was done via DataCamp courses that included select, from, where, joins, group by, subqueries, etc. 

There was also a small project that tested these skills, but there were no comprehensive projects.  I finished this topic feeling like I could write a basic SQL query but not go much further. 

4. Visualizing data with Python

This was also done using DataCamp.  I think learning a programming language requires a lot of practice, which I did not get with only doing DataCamp. 

In our second large project, we had to use Python to analyze and visualize our data, so we got some applied practice there. 

I basically felt like I had to relearn and teach myself python when doing my second project because DataCamp and applied python to a project are two totally separate experiences. 

Project Experience

Projects were of our own choosing. We chose the dataset (Kaggle or something) and the underlying question we wanted to tackle. We had individual mentors that would help us decide these things.

I would say it was as challenging as you wanted to make it, although I’m not sure what other people did as projects or how hard other mentors pushed people.

The first project utilized Excel and Tableau, while the other used python and Tableau.

At the end of the project, we presented to the graders our 10-15 minute presentation, which I think probably passed everyone although it was intimidating.

I hope you are finding this Springboard Data Analytics Review interesting!

Cost & Duration Of Springboard’s Data Analytics Course

Cost: $6000

I paid roughly $6000 for the 3-year loan, which was near the price of the course. I think the price is similar to other courses when I was first researching this.

I felt like it was overpriced for the amount of material, but I do appreciate the job resources (and job coach).

I feel like navigating my way through finding a new job and getting a certificate “heavy” enough to get a new job, I needed to pay that much money. (In addition to the coursework, job finding content was also added.)

You also get a full refund if you follow minimum job-seeking requirements and don’t find a job within 6 months of finishing the course.

Part of this job guarantee involves passing a mock job interview and technical interview that aren’t very hard but you must pass.

Duration: 6 Months

The course took 6 months, and for someone with a full-time job, it was a fair amount of material and projects to go through in that time, but after finishing I felt like I was underprepared and wished I had more practice on the aforementioned course topics.

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Pros and Cons of Springboard Data Analytics Program

What I liked about Springboard:

I liked the fact that after the program you get access to a career coach for 6 months. I felt like they were really invested in you not only finishing the project but also getting a new job.  I also like the idea of doing two large projects completely independently instead of doing prepackaged projects.

What I didn’t like about Springboard:

We were assigned mentors (industry professionals), in which we discussed the course once a week. I found my mentor to be friendly but not really a professional in anything besides Excel. I also felt like I didn’t have enough practice in any of the topics.

I also wish I’d had more guidance for the projects, although I understand why they wanted us to do them independently.

Maybe that was just my mentor. I don’t mind the fact that the material was outsourced from other websites, but I wonder why it was that expensive when they’re essentially just giving us links for instruction.

Also read: Lambda School Data Science review

Conclusion: Is it worth it?

I can’t say I recommend it compared to other courses, and I don’t feel like I got my money’s worth.

However, I do recommend it in the sense that if you want to change your career drastically without going back to college, you’re probably going to have to learn something in a structured manner and get career coaching to promote yourself (considering you may be sort of underprepared or you have no degree to prove you learned a lot of things).

I hope this springboard data analytics review post has helped you to make an informed decision about which data analytics course is best for your needs.

Notes: I also learned about basic statistics, mostly from Khan Academy. I felt very unprepared in this area. Although I did learn the basics, I felt if I took a basic statistics final test I might not pass. 

We also learned about basic financial measures (like EBIT) and economic constants (like elasticity), but I thought the program barely touched these topics.

Emily Rice

Data Analyst | Business Analyst | Relocating to Atlanta, GA – Excel | Python | SQL | Tableau | Data Visualization. Connect with me on LinkedIn.

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