Machine Learning Engineer - Zero to Hero
Updated: Aug 8
11/04/22 - This is a WIP post. I will update it regularly as I complete new courses so you can follow along.
So far I've been following a pretty chilled out game plan when it comes to infiltrating the AI field. I've been finding a few courses here and there and working on the projects that I find most interesting. The problem with this is that there is are SO many materials and courses out there, it's easy to get distracted...
In my first post I set aside a good 5-10 years to become an expert in the ML field. I'm basically starting from scratch and I realise it will not be easy. I won't get there without a specific plan so I need to make one! Thankfully I love the mornings so I've been using this time to do my courses and learn new things before my day job.
Today I've been doing some further research into the fundamentals I'll need to become a Machine Learning Engineer. This post will outline my current progress, as well as the plan to get where I want to be.
The goal: Become a machine learning engineer/ expert
The timeframe: I have 2 years to get my first role (April 2024 - I'll be 33)
Quick question, what is a machine learning engineer?
Machine learning combines pattern recognition and predictive analysis with computational statistics to teach computers how to identify patterns and predict outcomes. Essentially, by training a computer with data about different things, you can teach it to discern between them.
Machine learning lies at the heart of emerging technologies like facial recognition, gene therapy, and artificial meat. New applications are invented every day as companies vie to find the next hot innovation. The field has become so popular that machine learning engineers have the largest job market in 2021. - Codecademy
Python fundamentals were the top of my priority list for a long time. This is the language i'll be using and as a non-coder, I had to start somewhere.
So far I have complete the following courses:
Learn SQL - Codecademy (June 2021)
Learn Python 3 - Codecademy (July 2021)
Intermediate Python - DataCamp (March 2022)
As I write this, I am also in the middle of the 'Build Chat Bots with Python' on Codecademy course. The first section on rule-based chatbots was SUPER interesting, but I feel I need to solidify some other fundamentals before I go any further. I need to be super comfortable coding basics in python and for this I need more practice.
I've realised that an understanding of computer science, a knowledge of data science, pandas, and maths are all key components of a Machine Learning Engineer. As a result, I am going to tweak my learning path slightly and defer to the following career path on Codecademy; Data Scientist. The best part; they've just updated it to make it more relevant. As a digital marketer, learning these new skills will also help in my current role.
This covers python fundamentals again but with some more off platform portfolio projects. It also allows me to get stuck into a full career path on ONE platform. This means I have a structured learning plan for the foreseeable and am also paying for only one 'tool'.
Alongside the fundamentals, it will cover data acquisition, SQL and web scraping. There's lots of cool projects I'd like to code right now, but need to learn this to get started.
Next, there is a full section on data manipulation, pandas and matplotlib. I have studied some of this already, but the practice and application is what I need the most.
The rest of the course covers more in depth concepts and further exploits in natural language processing (something I've touched upon in the chatbot module). To top it all off, it ends in multiple modules covering the foundation of both supervised and unsupervised machine learning. In a nutshell, this new course builds the fundamentals and essentially leaves me exactly where I want to be. It has also been designed to make me ready for a junior role as a Data Scientist, so win:win.
Courses In Progress:
Data Scientist - Codecademy