Kce Process

ML Academy has been teaching hundreds of students Data Engineering on Google Cloud, AWS, and Azure. Many of these people have successfully completed their certification exams and also got satisfying jobs in the industry. We have a very high success rate of the participants who complete our process, some of the quotes are given below. Based on our experience and our philosophy we have developed the KCE Methodology® for getting jobs in Data Engineering. KCE Methodology assumes a strong foundation in Programming and SQL skills. Building on this foundation we emphasize on Knowledge, Certification, and Expertise (KCE).  Optionally for some, we also conduct Interview Prep sessions.

Tenets of the KCE Methodology

Knowledge: We want to make sure the participants have strong fundamental concepts of Data Engineering with special emphasis on public cloud. We teach using in-person video classes and hands-on labs. The focus here is on tools and methodologies. Knowing what tools there are in the toolkit, which tool to use when and what its limitations are is key to success.

Certification: While knowledge is key to long terms success, having a certificate from a reputable certifying body is essential for gaining industry recognition. Post knowledge we encourage all our participants to get certified and we help them prepare for the exam. We have a higher than 90% success rate in the first attempt for students who go through our process and give the exam.

Expertise: This is where the rubber meets the road. While certification can get you an interview, the jobs are offered to people who not only have the knowledge but can demonstrate that they have applied the said knowledge in solving real client problems of sufficient magnitude. CloudKarya, ML Academy’s consulting arm, has many client case studies where our students have demonstrated their skills. We offer our participants opportunities to work on such projects to enhance their expertise and their resumes.

Interview Prep (optional): Finally we prepare candidates for interviews. We show them how to prepare their resume, the LinkedIn profile to attract good employers. Further, we prepare them for phone-screening calls, in-person interviews, and salary negotiating skills.

Eligibility for the Course

We expect people to have sound foundational knowledge in three key areas:

  • Python Programming: While there are many programming languages, such as Java, C, Scala, R that data engineers use, we want to make sure you are familiar with Python. Python is increasingly becoming the industry standard and has a predominant market share.
  • Unix Shell Programming: Learning Unix shell command and being able to do basic bash scripting goes a long way in being able to do hands-on courses.
  • SQL Basic and Advanced: Knowing basic SQL programming is essential to be a data engineer. Knowing complex joins and writing SQL procedures is an added advantage.

We conduct a simple test for people who join this course and based on that we suggest a refresher course if need be.

Some Quotes from our Past Students

Here’s what a few of our past students have to say about KCE Methodology:

“I recently left a job with nothing else lined up. I was on a student visa tied to that job so I had six months to get hired and land visa sponsorship. Then COVID-19 hit. ML Academy  helped me land a Data Engineer role at a leading tech company, AND H1-B sponsorship during the pandemic.”
– Siva

“I was looking to get back into the workforce after taking 8 months off to pursue a startup idea. KCE Methodology helped me land multiple $100,000+ job offers within 3 months.”
– Ryk

“ML Academy helped me make the jump from a Program Manager role at Legacy company to a Data Engineering role with a $200,000+ compensation package – a 30% increase over my previous salary.”
– Amish

“I spent years struggling to take the transition from vendor to full time employee. ML Academy and the KCE Methodology helped me land a job as a Data Engineering job at a Fortune 30 tech company with a $40,000+ raise.”
– Adnan

“ML Academy helped me make the transition from Europe, to USA. Moving from Europe was not easy. But with ML Academy’s  help, I landed multiple offers in Data Engineering jobs and ended up accepting my dream job in Silicon Valley.”
– Sumati

Check out here for more testimonials. 

Conclusion

All in all – the best way to learn Data Engineering is by following  the KCE Methodology. Gain domain knowledge, get yourself certified, and solve problems to gain expertise. To aid you in this process’ successful execution – you need a mentor.

We recommend signing up for in-person or online classes where you’re in direct contact with your mentor. Learn actively, engage with colleagues, think of ideas, and share those ideas with people to ensure your growth and make it fun to go through this phase. 
Reach out to [email protected], or set up a call by choosing a 10 minute book-a-meeting with one of our instructors.