AiCore Specialist AI and Data Career Accelerator: Why?
At the beginning of my journey to NLP engineering, I surfed the Net extensively 🏄, took notes on the numerous online resources to learn the missing contents I needed for my profile to become attractive to potential industry employers, talked to all the techies I know, and obsessed over absolutely everything (such a hard choice 🤯).
What does a language professional with extensive experience in research need to become a competitive NLP engineer/researcher? Basically, the following, in this exact order:
Intermediate to advanced programming (ideally in Python, the most used programming language in the NLP industry);
(Deep) NLP techniques.
I covered the learning of intermediate Python by enrolling in a nanodegree by Udacity, Programming for AI in Python, which I am not far from completing. Those interested can read about it in my previous blog posts. As for (Deep) NLP techniques, I have already decided that I will take the Udacity nanodegree Become a Natural Language Processing expert nanodegree, the Natural Language Processing Specialization by DeepLearning.ai, as well as numerous short courses that I will be discussing and reviewing here over the upcoming six months (stay tuned! 🤩).
This blog post is about the reasons why I chose AiCore for my training in AI and Data.
Importantly, this post is not sponsored, endorsed, or administered by AiCore in any way.
AiCore is a career accelerator aimed at those who wish to move to AI and data. Concretely, it is an intensive training that lasts about 18 weeks, during which one learns about industry-standard tools and works on 4 capstones to become industry-ready and launch their career in a specialism of their choice.
Conveniently for those who do not live in London and/or are working professionals, the AiCore training is done 100% online. Differently from most trainings and online bootcamps, AiCore offers live learning Monday to Thursday, from 6:30 to 9:30pm. The latter was a major reason behind my choice to join AiCore.
What do you learn at AiCore?
The training in AI and Data offered by AiCore teaches industry-standard tools that include but are not limited to:
Software engineering (Git & GitHub, advanced Python, algorithms & data structures);
Data engineering (SQL, data lakes, data warehousing, web scraping);
Data science (Data cleaning, pre-processing & visualisation, A/B testing, feature engineering, statistical modelling, model selection and implementation);
Cloud Engineering (cloud computing, designing and building APIs, Docker, Apache Airflow, AWS Serverless Stack).
The trainee is invited to learn by working on multiple industry projects throughout, which include a game of hangman to go over basic Python syntax, and then a computer vision application, a web scraping project, and a specialist project.
The training is divided in two parts:
SOFTWARE AND CLOUD ENGINEERING ESSENTIALS:
The command line;
Git & GitHub;
Data formats and processing libraries;
APIs and web-scraping;
Algorithms and data structures;
Software design and testing;
Containerisation with Dockers;
Essential cloud technology;
Three portfolio mini-projects are completed during this part of the training.
SPECIALISM (at least one of the following):
Machine Learning Engineering
1 real industry system experience is done during the specialist part of the training.
A quick overview of what's covered in the different specialisms is provided below:
I will discuss the specialism that I will chose for me more in detail in a future blog post.
What's so special about AiCore?
AiCore doesn't just feed you technical knowledge, but it teaches you how to do things by getting your hands dirty. Throughout, the learner is invited to complete capstone projects in which they learn by doing. The instructions for completing each tasks are simple: try doing it first, google it, look it up on Stack Overflow, ask for support, and then and only then do take some time to go through the lectures and notebooks to learn some theory about it.
"What I hear, I forget. What I see, I remember. What I do, I understand." Xunzi (340 - 245 BC)
Accordingly, the portal revolves around one's current capstone. The picture below shows what the portal looks like when one's working on their first project, Hangman. Note the progress timeline right above the current scenario.
Inside the current project's page, the learner is provided with all sorts of instructions needed to complete the project, as well as the links to the prerequisite lectures and materials needed to succeed. An example, again from the Hangman project, is given below:
Of course, despite the hands-on nature of the training, the AiCore portal also features lectures, learning notebooks, and practicals that trainees can work on at their preferred pace. Deadlines are provided, although these are only indicative and can be modified easily. The current macro topics to be learnt on the AiCore portal can be seen in the video below; note that each topic includes numerous modules.
Some lectures are available on Youtube for those who might want to know more before enrolling. Here's a sample one:
The instructor in the video above is Harry Berg, one of the founders of AiCore.
Upon enrolling, the learner receives an invitation to access the portal, and one to join a dedicated Slack channel. Both can be used to obtain additional information about the training, chat with fellow trainees, and discuss hiring opportunities. The Slack channel looks roughly as in the picture below:
Every day, the AiCore bot sends all users a message with the evening classes programme:
Additionally, the AiCore portal comes with a very handy 'get support' button which can be used for matters of different urgencies that are forwarded automatically to the AiCore engineers and instructors. The pop-up window that appears when one hits the 'get support' button can be seen below:
Being able to receive quick and efficient support throughout the week is a terrific feature that is only offered by little other trainings I know of. On top of this, the AiCore community are in general quite friendly and keen to help - most trainees even stick around to help once they're finished with the training!
What should I take into consideration before enrolling?
Despite the attractiveness of the AiCore training in AI and Data, there are a few things that one should consider before enrolling. I discuss these in what follows.
The AiCore training requires a commitment of about 20h a week, which includes the live sessions, the time spent working on projects, and the learning done using lectures and various other materials from the Portal. Therefore, if you work full-time such as myself, you have to be sure you can make time for the training not only every evening but also at the weekend. This being said, the learning is self-paced at AiCore, and while there are deadlines, absolutely no one want you to rush through the material to get things done.
The AiCore training comes with a price tag of about £6500 to be paid upfront. For those who do not have savings, it is nonetheless possible to spread the cost of the training over up to 24 monthly instalments, for a total of £8750. Up-to-date information about the learning packages offered by AiCore can be found at the following link: https://www.theaicore.com/tuition.
The AiCore training is absolutely worth it. One of the things that struck me the most when I was about to make my final choice on how to learn AI and Data is the fact that literally every AiCore alumnus told me that they were overall happy with the training, and felt that it was basically the main reason why they managed to get hired quickly in the field of their choice, and with the attractive salary they hoped for. This for me was very reassuring, as the other trainings I was interested in all had a whole lot of unhappy alumni and students. How cool is that? For me, it was definitely the clincher.
I really hope that you liked this post, and hopefully I'll see many of you among us AiCore students in the upcoming months! As always, do not hesitate to share your thoughts here or contact me on LinkedIn if you have additional questions 😊
Until next time,