Can machines think? Can they behave like humans? Machine learning, an intersection of computer science, data analysis, software engineering, and artificial intelligence, is defined as a field of study that gives computers the ability to learn without being explicitly programmed. A Machine Learning Engineer is someone who builds programs that help machines to analyse vast amounts of data, and to carry out tasks with little or no human intervention. This is a fast-rising field of computer science that is behind such exciting technological breakthroughs such as the much-hyped self-driving cars! Other everyday uses include practical speech recognition as found in Siri or Cortana, Google Translate, and spam filtering.
Everywhere insight from data is required.
- Software Engineering
- Fraud Detection
- Marketing, Online Advertising
- Stock Market Analysis
- Healthcare / Medical Diagnosis
- And very many others
According to Jason Brownlee of Machine Learning Mastery, you don’t need a university degree to choose this path. There are a plethora of resources and training opportunities – online and in-person available to you.
However, getting a degree in Computer Science, Statistics, Mathematics, or Electrical Engineering may be enough preparation for you to dive into the world of machine learning as you’re unlikely to find a university undergraduate course in Nigeria or elsewhere. Masters and PhD programs exist in foreign schools like Carnegie Mellon University and others.
Want to power up your machine learning skills? Enroll for a free online course in machine learning on Coursera or sign up for the email course on Machine Learning Mastery. The latter lists other online platforms offering courses in machine learning and data science. Bookish types should also check out the relevant section. My advice: read Jason’s how to get started with machine learning post + comments.
A Potential Mentor for Those Interested
I found a Nigerian pro! You may follow Ikechukwu Okonkwo for his thoughts and resources on deep learning and machine learning.
Please feel free to post questions and comments here.