Springboard

I'd say the best parts of the Digital Marketing Career Track were the direct experience running Facebook Ads and Google Ads campaigns. You get hands-on experience using $100 budgets and up to $10,000 if you participate in the Google Marketing Challenge where you work with a real non-profit which is invaluable. In addition, you can talk to your mentor each week and they'll help answer any questions you have regarding these projects. I also appreciated the career  services, especially since you have access to the career coaches for 6 months after you complete the course to help you find your perfect job. 

This program has many great resources to help you advance your skills as well as a curriculum that keeps you focused and scheduled in completing your work. There is a community of people looking to help you including career coaches, weekly mentor calls, which I used to discuss the projects I was working on as well as specific questions about coding. And an online forum of students asking questions pertaining to the same types of projects you are working on. The main focus of the course is completing two main capstone projects which are geared towards building your portfolio and are exemplary of work one may do in a data science career. While there are many smaller mini projects included in the course that are also good practice to improving python and sql skills, there could be created content designed for learning the code and applications needed in these types of assignments. A significant portion of the curriculum was just courses on DataCamp and video lectures, while informative, are not particularly useful in grasping the concepts needed. For an expensive course, I was expecting more specialized resources focused on learning the skills needed, rather than just projects that force you to know the material and go out and use it, which is difficult at first and slowed my progress throughout the beginning of the course. I viewed this as being both a good and bad thing, because although I began working on these projects without all the necessary knowledge and skills, it forced me to pick them up as I went along.

Pros:
- dedicated mentor
- can schedule calls with random mentors for problems your having with very open times to choose (super helpful)
- access to datacamp and linkedinlearning (my favorite platform to learn data is from datacamp personally)
- Excellent administrative team
- Excellent career support team with advice well in line with reality, always super friendly
- Show you how to network properly
- Annual springboard rise event
- Involved student community

Cons: 
- too much use of videos and not enough use of reading for many of the subjects. Many of the topics could have been better explained from a book or article than watching many of the webinars from Harvard or pycon in my opinion. Those videos were often very lengthy and hard to follow along with and I found myself skimming through them. They didnt have decent background information before the these videos that would delve into complex subjects sometimes. This is my biggest complaint to be honest. 
- Some of the assignments needed better instructions such as the databricks miniproject. I know trying to figure something out yourself is the best way to learn but when you dont have the 
preknowledge on something so new to you it could be frustrating

Summary:
Springboard was exactly what I needed as someone coming from a background in business and who had next to zero technical skills such as coding. I landed a role as a  contingent worker  at Facebook as a business data analyst. Without a masters degree or more extensive work experience in tech working with data, i still havent been well suited for a data scientist position, so I'm supplementing this with starting a masters degree program in data scientist, but I believe if you already have a masters in any field and or have remotely relevant experience working with data, a masters degree wont be needed to land a data scientist position like I think is needed for me. Springboard is overall an excellent program to learn. 

After getting my Ph.D. last year, I started to study about data science and get some online certificates. However since I had a full-time job as an Electrical Engineer, it was pretty hard to find the right materials to study or build my portfolio in Github. I got lost after a few months, and there was no support and feedback.  When I found the Springboard career track program, I found it a matching base on my interest and my background. The  1:1 mentor calls every week, was excellent support and pushed for me. The other advantages were about the four mock interviews that Springboard provide to get us ready for the real interviews. 
I recommend this course to people who have a good background in coding and have some knowledge about machine learning since it is an intense program and you have to invest proper time and effort in 6-8 months. 

I just completed Springboards Data Science Career Track Bootcamp. Overall I was very satisfied with the experience. The skills I learned are super useful, and make me much more marketable as a job applicant. The 1-on-1 technical mentoring was great, helping me overcome obstacles and prioritize my time. The career coaching was also very valuable, helping me improve my resume, cover letter, etc.

Some of the chapters in the curriculum simply pointed to youtube videos, which often (though not always) excellent at explaining data science concepts. Some of the chapters linked to Datacamp courses, which are often a little too easy but do explain the concepts well. Overall, the miniprojects and capstones were great, and helped me learn all the steps of being a data scientist.

Granted I don't have a job offer yet, but their job guarantee certainly provides some peace of mind. 

I started this program to brush up on my Python skills, as I had worked in financial analysis before and was looking for a data analysis position. Most of my data analysis before had been done in Excel, with some small Python projects.

The 3-month program had a curriculum consisting of mostly third-party materials - Youtube videos, academic videos, code exercises with first-party supplements, and of course a lot of coursework/projects. You also have weekly calls with a mentor who helps you navigate the materials and gives industry insights.

The curriculum definately boosted my Python skills to the next level, while giving a good introduction into Data Science concepts. In my opinion the Machine Learning segment was a little light, but it gives you a good foundation for further research and learning.

And yes, I was able to find a position in the field even before finishing the program!