Data Application Lab

This program was very challenging to me. There were times that I thought I would not make it through and wanted to quit. I had to remind myself that this program is only introducing me to the various plethora of tools in data analytics. Some tools I have heard of and other I had not. There were some of the concepts and tools that I would never seek out and there are those I want to learn more about. To be successful in this program, you will need to be committed. You need to understand that there will be things you will not understand but you need to push through it. Use all available resources. I like attempting the challenges and when stuck, I will have something for my tutor to help me resolve. That is something I did not realize until later in the program. You will definitely need two monitors! Attend office hours before and after class. The instructor and TAs were very helpful when I had an issue. Set your time for working on the assignments and stick to it.  You have to remind yourself that it is only temporary and not a life sentence. Read through the requirements of the challenges before submitting. Take advantage of resubmitting your corrected assignments. Realize that the instructor is fallible and the topics maybe challenging them to teach. They have topics that they are more knowledgeable about than others and this program is the only teaching experience they have. This program will solidify soft skills such as: critical thinking, problem-solving, time-management, and team building. As challenging as it is, try your best to remain until the end. It's completing and not always about getting the 'A'.

I took the DS bootcamp during October, it was a great bootcamp which had almost all industry requirement to build up your technical skills and helps you go through techncial interviews. If you are really looking forwards to step into the data world, the bootcamp could be your choice. It can also helps you get familiar with some big data platform such as Hadoop, Spark and Hive. The most effective way is the instructors will take you into some experiences of the Kaggle Competiiton, whihc will ensure your Python skillls and furthermore.

This is an overall good learning experience with an intense schedule.

The most important highlight is its practical view of the industry, as the materials comes from real world data and projects and the instructors have in-depth knowledge and experiences in industries.

Also, with a diverse composition of students, some whom are students like me and some of them are young professionals, I also gain insights of how the career development process could be like.

As a plus, the course also include ineterview trainning sessions, which is useful. Those suggestions from past experiences are good starts for my preparation for job interveiws.

In all, this course is a bridge for me, as a graduating student, to the real world working environment.

Though a couple of teachers are pretty good, the overall course fails short of my expectations,

1. the big projects aren't very helpful. some teacher are not familar with the project thus can't help the issues we encountered.

2. The boasted clusters are only for limited usage ( hive query ), it is not for big data experiments such as spark jobs, etc.

3. the sales guy were vague about the choice of elective projects but actually it is very rigid, you can only choose 2 projects.

4. there is limited chance to get an internal reference.

5. very limited help from instructor after the course. You get answers mostly from other students and teaching assistant. rarely from instructors.

Overall, I don't feel it worth my money.

I really recommend the business analytics course and data scientist course at Data Application Lab.

I took these bootcamp in 2018. The courses are perfect for students who want to pursue a career in data science field but don't have education background. 

I did several hands-on projects in the bootcamp, in which we would use statistical modeling and machine learning algorithms to solve real business problems. Those projects have allowed me to drastically expand my data analytics capabilities and programming skills.

In the data scientist course, the instructor would teach us how to master the Kaggle competition with the advanced algorithm and innovative models, such the motheds are unique from industry that I couldn't find anywhere else online. I participated the Kaggle competition with the guidance of the instructor and the TAs, and got an awesome place. Finally, I got a lot of job interviews because of the Kaggle experience I put on my resume.

 

I started the DS course in last August. In order to balance between my schoolwork and the DS training course, I made a lot of efforts.  The instructors taught a high volume of DS knowledge every class. I need to review and practice in time to remember all the points they made. If I got questions, the teaching assistant would kindly help me. There are two Q&A sessions every week. What I found most valuable about the course is the high-profile data science projects, which guided me to apply the knowledge in practical areas. Most importantly, the program also includes resume critic and job referral opportunies which helped me get my first Data Analyst internship. I really appreciate the service and help accompanied with the course.