In the following paragraphs, I would be sharing the journey that I have gone through and some tips and tricks that I have picked up. If you are thinking of going down this path, just like what I did three months ago, please continue to read...
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Data Science Immersive Bootcamp (Full Time, General Assembly)
step 0 : Application
- Go to https://generalassemb.ly/education/data-science-immersive/singapore to find out the syllabus, dates, course fees. *If you are above 40, you will enjoy higher subsidy!
- Click on 'Apply Now' to fill in the application form. A GA Admission Producer will contact you shortly to chat with you on why you want to take up this course and if you are eligible for the IMDA TIPP subsidy. *For my case, she actually called me within 30 mins after I have submitted!
- Note that If you are taking up the IMDA TIPP subsidy, you will have to secure a full time data science related job within 6 months from the date of graduation. For details, please check with GA or IMDA directly on the terms and conditions.
- You will be asked to complete a short data analysis assignment (some Excel data) and prepare a short presentation on your findings to be submitted to the admission producer. This should not take you more than 2 days to complete.
- You will have to meet the admission producer at GA office to go through your assignment and to confirm your enrolment.
step 1 : Enrolment & Pre-Work
- Once your enrolment is confirmed, you will have to sign a student contract and make arrangement for the payment of course fee (full payment or by instalments).
- You will receive email from the GA student service officer on steps to complete pre-course training material. This training materials comprises diagnostic assessment, pre-work and job-readiness outcome tasks.
- The pre-work covers basic python syntax and maths concepts on probability, statistics and linear algebra. It is about 15 hrs in total. *Please give yourself ample time to complete this pre-work. In fact, I find this pre-work a little too basic to prepare myself for the actual course content. I would recommend picking up some online courses on maths concepts (linear algebra, probability and statistics) and python for machine learning. You can find these in udemy, coursera.
step 2 : The 'Fun' Part (course commencement - first 8 weeks)
- You will have a class orientation (in the evening) one week before course commencement to meet your instructor, teaching assistants and to prepare your laptops (installations of all required software components (Mac or windows are OK).
- Your daily time table starts at 9am and ends at 5pm (Monday to Friday). Morning is typically used for covering of concepts by the instructors. Afternoon is for you to complete the labs based on the concepts taught earlier on. Labs are typically individual but sometimes they might practise pair programming which you get to work in pairs. You will have to be resourceful in googling for solutions should you encounter any difficulties in tackling the labs.
- You will also have to complete a project and present it to the class every 2 weeks. Each project is due every Friday of the even week. That is, project 1 (Due Week 2 Friday, individual), project 2 (Due Week 4 Friday, individual), project 3 (Due Week 6 Friday, individual) and project 4 (Due Week 8 Friday, group).
step 3 : Your Capstone Project (last 4 weeks)
- On top of the 4 projects, you need to also come out with your own capstone project ideas. Complete your capstone and present it on the last week of the course (Week 12) in order to graduate.
- You will have Flexi Time to work on your capstone project in the last few weeks of the course.
step 4 : Outcome Tasks
- The class will be assigned a career coach who will guide you on how to create your resume, linkedIn profile, GA profile and job search tips and tricks. Note that it is your responsibility to apply and secure a job upon graduation!
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course reflection:
- The most challenging part for me was the understanding of the underlying mathematical concepts behind the machine learning models. So make sure you are prepare for that if you not strong in that area.
- Minimise any distractions you may have and ensure you are able to fully focus on the course during the 12 weeks as the pace is fast and you are loaded with new content every day...
- Seek help early if you are not coping well. You will be surprised how helpful your instructor, TAs or your fellow classmates will be!
- Be prepared to burn your weekday nights and weekends to work on projects.
- Last but not least, enjoy the process of learning. It's not easy but I find the skills I learnt very useful!
That's all for this sharing. Hope you find it useful.
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