Data science has been a buzzword for some years now and a lot of people have been looking to join the train. This has led to a lot of learning institutions teaching data science at different levels.
Data science, machine learning, and artificial intelligence have been used interchangeably by some tutors and Hr managers. We will be looking at the difference between them.
Data Science, Machine Learning and Artificial intelligence
The tech space is growing faster than anyone has ever predicted, data is been generated in thousands of gigabyte per time, one thing that is sure is that when data collected is visually presented, there are always patterns and meaningful information can be gotten from it, What happens when data runs into terabytes per time and we need to get information from it like understanding the past and predicting the future? Enter data science.
Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.
With skills like programming and statistics, you will be able to create data models that take data and interpret them.
At a very high level, machine learning is the process of teaching a computer system on how to make accurate predictions when fed data.
Now you understand why data science is important, let’s take a look at how you can start a career in data science.
Learn a programming language
There are a lot of programming languages to choose from, but Python and R have been used a lot as the best programming languages to use in data science. Start with learning the concept of programming then move into getting comfortable with Python programming language by building mini-projects.
This is the fairly easier part, but very important. While there are packages in Python and R the make data visualization easier, it may be difficult to fully understand for beginners. Start learning to use data visualization with spreadsheet packages like Excel or Google, this will improve your understanding and help you develop your data visualization skill faster.
Improve your statistics skills
Take a course in statistics, this could be a refresher course that will help remind you of some concepts that you may have forgotten. The bulk of work done in machine learning is statistics. Although you may not be required to write formulas most times understanding them will help you a whole lot.
This is also very important in data science as you will be required to communicate effectively the findings from your analysis or predictions. You may also consider taking a short course on communication skills in data science while learning to code.
These are some of the important skills we will need to start a career in data science, Communication skills help present the data in a readable form, data visualization helps give an overview of the data and programming skills plus statistics skills help build models that can use data for predictions.