Data is ruling the world, and it is also powering most of the technologies. While we continue to get amazed by the new developments of technology worldwide, we can certainly not miss the fact that there is a great demand for data scientists who can work on the innumerable data available with us. The work of a data scientist is to study this data and derive useful information from the same.
If you are also planning to make a career as a data science expert, then we have got this mini-guide for you. Here we have tried to cover all the points that will help you become an excellent data scientist.
Path to becoming a successful data scientist:
1.Start brushing up with your mathematical and statistical skills- One of the key skills that you would need as a data scientist is mathematical and statistical skills. Using these formulas, you will be able to derive inferences. Although, many software and tools will help in assessment, having a thorough knowledge of statistical and mathematics will give you an upper edge. Some of the key skills that you would need are inferential statistics, probability and exploratory data analysts.
2.Learn the programming language- Once you have gained an insight into the mathematical and statistical concepts, your next move will be gaining expertise in a programming language. The popular programming language that you need to know is Python. It is a versatile programming language that finds a multitude of applications across different technologies like artificial intelligence, Big data, blockchain and others. So, it is not just Data science that finds Python's use, but you can also use it across different segments.
3.Learn about the basics of machine learning- To become a successful data scientist, one also has to learn about machine learning. When you learn about the basics of machine learning, you also learn about the concept of logistic regression, decision trees, support vector machines, and linear regression, which will be helpful for you in your data science course.
4.Natural Language Processing (NLP)- The primary reason we are focusing so much on Natural language processing is that in the end we will be using the data and preparing algorithms to drive the machines to work as a human, and it is possible only when you know about NLP and its frameworks.
5.Neural Networks (and Deep Learning): If you are learning about machine learning as a part of your data science certification preparation, you also need to learn about neural networks. The wider adoption of deep learning applications, it becomes an integral part of the data science learning path. Yes, deep learning is part of the data science learning path.
These are some of the basic steps that are going to help you become a data science expert, and if you too are willing to join the bandwagon, then the time is now. You have to enrol for a data science certification program by the Global Tech Council to become an expert in this domain. Connect with the Global Tech Council to know more about data science certification programs.
