Absolutely resonate with the sentiment of prioritizing practical skills in ML. Many ML courses fall short in delivering the day-to-day essentials for real-world work. Excited to find a course that truly equips you to excel as an ML engineer
I understand! I realize it may not be the best time for many people, but in my opinion, the most important will be working on the homework. I will record every session and I will add pre-recorded videos. We will be able to work all together asynchronously on the online community.
Thank you, Damien.Can you please advise with your honesty and how best this course will be useful to refresh my knowledge in data science targeting FAANG companies in mind, where I am looking for career growth in director/principle level roles? I am a principle data scientist. I have 17+ years of industry work experience in building scalable software applications and products, and for the last 8 years I have been working on AI and ML use cases. As you know, we have seen the adoption of AI in industries and the struggle we faced in our early careers with ML to convince C-suite people, and now with generative AI, things have changed. Now, every single executive in the organization is at least thinking about it and talking about it daily to consider genAI for every single use case for the product and application implemented. Recently, I have been following your work and newsletters, and they are unique and content-oriented. and it impressed me a lot to learn. I am trying to continuously learn to crack interviews at FAANG companies. Mainly focused on Google, Meta, Apple, and Netflix. Please advise.
First of all, be aware that the "data scientist" position in most FAANGs don't work on ML. They tend to be more data analyst than not. Some work on ML but it would be more prototyping than anything else.
When it comes to preparing for FAANG interviews, it won't be the right format. There are tons of companies that specialize in preparing for FAANG interviews, and personally I am not too interested to focus on that right now. FAANG interviews for ML engineer positions require grinding Leetcode type problems, and preparing for system design and ML system design interviews. I will cover the ML system design because the interview format is very close to what is useful on the job, but it will be limited when it comes to fully preparing for interviews.
I really want to focus on making people better in ML to work in the field. I tend to think about this bootcamp to be similar to an academic experience, but with content that is actually useful on job.
There are many other ML tracks I want to develop before I work on a bootcamp for interviews. If I don't see you in this bootcamp, maybe I'll see you in a future track! Good luck for the interviews!
Very nicely said. Thank you for your honest advice and looking forward to joining with many of your courses and learn more for better future and community help!
Hi Damien, Good day! Do you have any road-map that the courses which you are planning to launch and you would be teaching in coming months. I would love to hear from you, if possible it might for my learning plan. Thank you for awesome educational teaching.
Absolutely resonate with the sentiment of prioritizing practical skills in ML. Many ML courses fall short in delivering the day-to-day essentials for real-world work. Excited to find a course that truly equips you to excel as an ML engineer
How will the HW project’s difficulty be? Is it full-fledged projects? Also when will course recorded lectures accessibility ends?
The lectures will always be available. The projects will be homeworks to help understand the concepts.
Absolutely resonate with the sentiment of prioritizing practical skills in ML. Many ML courses fall short in delivering the day-to-day essentials for real-world work. Excited to find a course that truly equips you to excel as an ML engineer
Can We start on Evening . Considering all TimeZone .
Unfortunately, I am not available on evenings!
Damien - For professional learners 9 am PST is hard on week days. Do you think you can plan for evening for week days or weekends?
I understand! I realize it may not be the best time for many people, but in my opinion, the most important will be working on the homework. I will record every session and I will add pre-recorded videos. We will be able to work all together asynchronously on the online community.
Thank you, Damien.Can you please advise with your honesty and how best this course will be useful to refresh my knowledge in data science targeting FAANG companies in mind, where I am looking for career growth in director/principle level roles? I am a principle data scientist. I have 17+ years of industry work experience in building scalable software applications and products, and for the last 8 years I have been working on AI and ML use cases. As you know, we have seen the adoption of AI in industries and the struggle we faced in our early careers with ML to convince C-suite people, and now with generative AI, things have changed. Now, every single executive in the organization is at least thinking about it and talking about it daily to consider genAI for every single use case for the product and application implemented. Recently, I have been following your work and newsletters, and they are unique and content-oriented. and it impressed me a lot to learn. I am trying to continuously learn to crack interviews at FAANG companies. Mainly focused on Google, Meta, Apple, and Netflix. Please advise.
First of all, be aware that the "data scientist" position in most FAANGs don't work on ML. They tend to be more data analyst than not. Some work on ML but it would be more prototyping than anything else.
When it comes to preparing for FAANG interviews, it won't be the right format. There are tons of companies that specialize in preparing for FAANG interviews, and personally I am not too interested to focus on that right now. FAANG interviews for ML engineer positions require grinding Leetcode type problems, and preparing for system design and ML system design interviews. I will cover the ML system design because the interview format is very close to what is useful on the job, but it will be limited when it comes to fully preparing for interviews.
I really want to focus on making people better in ML to work in the field. I tend to think about this bootcamp to be similar to an academic experience, but with content that is actually useful on job.
There are many other ML tracks I want to develop before I work on a bootcamp for interviews. If I don't see you in this bootcamp, maybe I'll see you in a future track! Good luck for the interviews!
Very nicely said. Thank you for your honest advice and looking forward to joining with many of your courses and learn more for better future and community help!
Hi Damien, Good day! Do you have any road-map that the courses which you are planning to launch and you would be teaching in coming months. I would love to hear from you, if possible it might for my learning plan. Thank you for awesome educational teaching.
I have a plan but I prefer to take it one bootcamp at the time. I will communicate later about it.
Absolutely resonate with the sentiment of prioritizing practical skills in ML. Many ML courses fall short in delivering the day-to-day essentials for real-world work. Excited to find a course that truly equips you to excel as an ML engineer