My Experience from Solving Complex Problems

Ziyaad Parker
5 min readJan 10, 2019


Problems don’t knock when they approach you neither do they show any sign they are coming. Thus everyone should be prepared on how to solve these problems when they approach. In life there are complex problems which you encounter and feel as if your mind has failed to function or it has collapsed. But at the end you get a solution to the problem. Everybody at one time or another faced a complex problem in life. This makes it important to learn and understand skills of solving complex problems. Don’t wait until that moment when you are faced with the problem you seek to know how to solve. From my experience there are three key skills which assisted me in solving complex problems. They are all computer science related skills and they really helped me in puzzle situations.

What are complex problems?

It is very hard to really say what or define complex problems as people have different opinions about the source, nature and to what degree is the problem. It is from social complexity that makes complex problems hard to address. However complex problems can be said to be questions or issues which cannot be answered by simple logical producers. It will require abstract reasoning application through multiple frames of reference.

The current talk that there are possibilities of machines to do things which humans or homo sapiens can do has left many perplexed. These machines are impacted traits and skills programmed into them which assist them solve many complex problems. These skills and traits are important because they help solve any kind of complex problem.

Computers were build to solve large complex problems. However the whole process is more understood if you understand computer science term but this article I will make it simple for you to understand. As various have used computer made machines to solve their disturbing problems so did I. When you use the correct algorithm and the program is efficient the problem will be taken care of and solved. That is the general rule used by computers to solve complex problems. Here are key points used by computer to solve problems.

Thinking like a computer scientist

Computer scientists combine various thinking skills to come up with a solution to complex problems at hand. Some of the best features they combine include mathematics, engineering and natural science. In mathematics computer scientists take formal language and denote ideas which are computations. Engineering takes design, assembling and evaluation. In natural science they take observation skills, form hypotheses and try predictions. The key significance a computer scientist owns is problem solving. This means he or she has the ability to formulate problems, think creatively on the possible solutions and state clearly and accurately the solutions.

To be able to learn the practice of problem solving the complex problems, it is important to learn the process of learning to code. The whole thing about learning to code is that you will be able to think like a scientist and you will learn python which is an example of a high-level language. It is different from low level language or the machines language. By jut understanding all about programming you will above built knowledge enough to solve any complex problem.

How to think like a Computer Scientist

Artificial Intelligence

Artificial intelligence is a computer science study which focuses on creation of intelligent machines that work and reacts like humans. The developed machines learn algorithm compare similarities between new entered incidents and historical data, suggests root causes and corrective actions for a quick and efficient solution. The development of artificial intelligence machines is now part of the technology industry.

For the machine developed there are core traits which are programmed in it for it to function as purposed to? In addition, engineering knowledge is also key part of artificial intelligence research. Some of the core traits programmed in these developed machines includes problem solving. There are other traits like knowledge, reasoning, perception, planning, learning and ability to manipulate and move objects. These traits are also essential in problem solving.

The whole thing behind artificial intelligence is the development of thinking machines just like human beings. On how they are developed to think like human being is a very long process which computer science terms are not easy to be understood. All important is to take the key traits the machines use to think and solve complex problems.

The definition of this term Artificial Intelligence as begun to shift based upon the goals that are trying to be achieved.

Deep Learning

Deep learning is a subset of machine learning where artificial neural networks, algorithms inspired by human brain, learn from large amounts of data. This is equal to how human beings learning from experience. Deep learning algorithm will perform a task repeatedly every time tweaking it a little to improve the outcome. Deep learning are used in solving complex problems because neural networks encompass deep layers that enable learning. Think of any problem which require thought to figure out a solution. One example is detecting diabetes using Deep Learning.

Just with the increasing amount of data we generate every day is a resource that makes deep learning possible. As deep learning algorithms require a ton of data to learn from, the increase in data generation is one major reason behind and making deep learning capable of solving complex problems resulting to its growth in recent years. More so, deep learning algorithms benefit from the stronger computing power that’s available today as well as the proliferation of artificial intelligence as a service. Artificial intelligence has given a chance to small organisations access to artificial intelligence technology and specifically the artificial algorithms required for deep learning which doesn’t require much initial investment.

One advantage of deep learning is that it gives a chance machines to solve complex problems even when using data that is unstructured, inter-connected or very diverse. The machines even perform even better when more deep learning algorithms are learnt.

How to generate revenue from solving a problem

This notion of making cash out of solving people problems as two main interpretations; it can mean directly earning revenue by operating consultations. It can also mean driving revenue from customers or clients by acting with a problem solving. All required when solving problems is that solving bigger problems earn more. Here are two ways through which you can make revenue out of problem solving.

Revenue from Problem Solving

Create a consultation business

This is where you start a consulting business by resolving customers or client problems. If the business grows bigger as are so many people seeking help to their problems, you can hire outside consultants to assist you and earn more. Before you think to start this kind of business be an expert to a specific field then you can start the business.

Add on selling service

As one problem leads to another you will sell one solution to his or her problem then comes again for another solution to a related problem. This will make you generate more revenue when you offer solution to the related problem. So have a solution to the related problem you always get to solve.