Zia Khan Brings Data Science Expertise to LearningFuze

What inspired you to make data science your career?

I come from a background in IT, data, and math, and I have over 20 years of experience in the IT field. My undergraduate degree was in computer science with a minor in math, and I have a master’s in computer science. I worked in Vancouver doing cloud computing and data center computing for about 10 years. Data science caught my attention in 2010 when it was first starting to pick up and there was a lot of hype about big data. I started looking into it to see if it was something I wanted to do for the rest of my career. With my technical background, I was actually able to land my first job in the data science field without going back to school. I did take a few courses here and there, and I watched a lot of tutorial videos. It was a lot of hard work, but I didn't need to take any specific courses or have a specific degree when I was trying to get that first data job.

What motivates you to teach the next generation of data scientists at LearningFuze?

It was actually a happy accident! A few years into my career, I was with a company that also taught a data science course. One of the instructors had a family emergency and had to leave for a while. I was asked to teach a few sessions so the continuity wasn’t lost and I discovered that I really liked it. I received good feedback from the students as well. It was such a success that I ended up teaching more courses and now I am teaching data science at LearningFuze. 

I like teaching because I’m able to help people who are trying to get into the field and I’m able to lead the transition. I understand all of the challenges that they have because I went through those same challenges and it took me at least a couple of years to create that foundation. I think that’s where I can help the students by understanding their challenges and guiding them a bit as well.

Why do you think data science is a great career in 2024?

Many people have said that data will be the new oil, and I think that is true. There is so much data now and companies want to take that information and get value out of it. As a result of AI, companies are relying on machine learning and the data it requires to stay competitive in a rapidly changing environment. This has only increased data. If you’re thinking about it, if you’re passionate about it, and if you have the opportunity, I think data science is a great field to get into now. 

What makes learning data science at a bootcamp like LearningFuze different from a college degree program?

College degrees offer great content and instructors and they can bring great value, but in data science, you need to also learn business knowledge and hard skills like coding and math are important. LearningFuze’s data science bootcamp excels at getting students to work on job-relevant projects. Having students work on these projects on a weekly basis helps them understand how data science can apply to a specific industry and what the benefits are.

How would you describe your teaching style?

I’m more of a hands-on teacher. I like for my students to actually do the work and I help them get on the right track without spending too much time on something. I like when students put in their own effort because to me, that’s how you learn. You need to put in the effort to learn a new skill. I always push my students to try and do a little bit more than they think they’re capable of. 

Do students have access to TAs in the bootcamp?

Definitely! Students can receive support from our teaching assistants during the evenings when there isn’t class time in addition to instructor support, and a data coach who leads engagement within our data science community.

What goes into the data science curriculum at LearningFuze?

We teach students data science from the ground up. In data science, you have to extract the data, then prep the data, and then you do the modeling piece and analytics. All of those phases of data science go into the LearningFuze data science curriculum in addition to machine learning and deep learning. It’s one thing to build a data science model and another thing entirely to implement it — at LearningFuze, we teach students both aspects.

We are a Python shop, so we focus on Python as a tool.

What kinds of projects are the students building in the data science bootcamp?

LearningFuze’s Data Science Bootcamp is a two-module program. Each module is 12 weeks and our goal is for students to complete at least 10 projects during that time. Student projects vary from healthcare to finance industries and they work on new datasets almost every week. We want them to get an idea of how data science is applied in a real-world setting with different environments, datasets, and industries.

Is there an ideal student for LearningFuze’s data science bootcamp? Do new students need a technical background to enroll?

The ideal student is someone who is willing to put in the work and effort. I personally have seen people from all different backgrounds go into data science. Anyone who puts in the right amount of effort realizes it’s not difficult to get into data science — it just takes work. 

While everyone is encouraged to apply to the bootcamp, someone with a broad knowledge of programming or coding and/or some background in math or statistics would do very well in this program. 

Does LearningFuze offer a prep course?

We offer a data science prep course that is open to anyone, but I highly recommend it to prospective data science students who don’t come from a STEM background. Since the Data Science Full Immersion bootcamp starts from a point where students know how to code, write a function, and understand data, LearningFuze’s data science prep course curriculum ensures that students have a foundation for the data science bootcamp. In the prep course, we give students a basic understanding of Python, statistics, and syntax, plus they start working on their first data project. 

How many hours a week do you expect students to commit to the bootcamp?

Our expectation is that students spend twice the hours outside of class studying. Class is held Monday through Thursday for 3-4 hours in the evening 

Monday, Tuesday, and Thursday are lecture-based, and Wednesdays are project-focused with assistance from the Junior Instructor. 

To be successful, students should spend another 3-4 hours outside of class working through the content and assignments. 

How do you assess student progress as they’re learning Data Science?

Students have to complete those projects to show they are progressing. In addition to completing the project, students must present their projects because that’s one of the skills required to land a data science job. Companies want to see that you can analyze your findings and communicate your findings. We also work with Kaggle where students can hone their thought process through competition. It’s a great way of finding out where you stand in your studies.

How do you help a student who is struggling or falling behind?

For those who need help with the curriculum, we offer a data coach, teaching assistant support, and mentorship. We want to make sure students understand the pieces that are missing or what is lacking in terms of their skillset. We closely work with students so we can catch any knowledge gaps fairly early. This is also why the project presentation portion of the program is important! We have students presenting their work within the first few days of the bootcamp, and that helps us gauge early on which students may need extra support. 

What kinds of data science jobs are LearningFuze graduates prepared for after they finish the bootcamp?

LearningFuze data science bootcamp grads will be eligible for roles like:

• Junior Data Scientist
• Senior Data Analyst
• Predictive Analytics
• Machine Learning Engineer

While some students may be able to land a data scientist role, that position often requires more in-the-field experience. Generally, roles that cover skills including machine learning and deep learning also align with the skills students gain from LearningFuze’s Data Science program. 

Is this data science bootcamp good for people looking to upskill from a lower-level data position?

I think this bootcamp is a great fit for those looking to upskill. Those students coming from an analytical background like Data Analysts, Business Analysts, Data Engineers, and even people coming from a SQL background will be a step ahead in this bootcamp because they understand how to analyze data. They will easily shift from data analytics to doing some predictive analytics to get a more senior job as a Data Scientist.

Do you have any favorite resources or meetups for beginners who are getting into data science?

Data science is similar to swimming in that you can watch a lot of videos, but if you don't get into the water, it will be hard for you to learn to swim. The first thing to do is start working with data, even if you’re doing it wrong. You will only start to get better once you start trying.

Kaggle is a great resource with many different datasets on their website. We are also piloting a self-guided Python course for students new to data analytics. To get access, fill out our contact us form. 

Find out more and read LearningFuze reviews on Course Report. This article was produced by the Course Report team in partnership with LearningFuze.