Systems Engineering Neural Networks, Machine learning with a “system” approach.
Course Description
Systems Engineering and Artificial Neural Networks? In appearance strange bedfellows, but deceitfully so. Over our lives, we spend a long time thinking about making the right decisions, but we hardly stop and think about how we do it. We do know that our brain processes millions of data simultaneously, and sometimes we do not even realize that a “synaptic journey” has taken place. Every day, we deal with problems that can be seen as optimizing complex “systems”.
According to IBM “Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.”
Naturally, this short course cannot cover all the contents of the reference material, but will cover the key topics such as the definition and engineering of neural networks. Then it will progress to the system thinking approach, with questions to help you reflect on what you have learned and apply what you’ve learned to your own project. So what do you need to follow this course? Thirst for knowledge, resourcefulness because the subject is complex, and it requires you to be proactive and go online to fill the gaps by reading articles and other resources, and even follow other online courses on the same topic. And of course, a great deal of patience because, as said, the subject requires some time to be fully mastered.
