Before entering into the world of data science and machine learning, there is always a question about the set of differences between all these closely related terms. Gaining data science certifications can be helpful in understanding these differences better. Let’s see how the two differ.
What is Data Science?
Data science involves the study of various types of data and extracting some meaningful information from them. This information can be used to analyze and make informed business decisions, thus increasing revenue. It involves tasks like data gathering, data insights, statistical analysis, data manipulation, leveraging AI to extract meaningful data. It doesn’t matter whether the data is structured or unstructured, small or large, data science can help with its analysis. It provides a platform to use different techniques and methods are used to enhance the business by using the extracted information. There are various jobs available for data scientists, and you can apply for them if you have any data science certification.
What is Machine Learning?
Machine learning is a part of artificial intelligence in which various algorithms and data are used to build applications or machines that learn from fed data. They are self-learning algorithms and help improve the machine’s efficiency and accuracy without programming. It is a system in which machines learn from the data and their previous mistakes. Machines are made to work, think, and act like humans. These algorithms can work on the initial given data, also called “training data,” and build various mathematical models. These models can perform multiple tasks, such as taking a decision without any prior coding or commands.
What is the relation between data science and machine learning?
Machine learning is a part of data science that includes using the data science stack to create different mathematical algorithms. There are many processes that a data scientist has to do, like data pre-processing and statistical analysis. However, machine learning does not require any elaborate or precise data to start the processing.
Although, it seems like machine learning and data science are the same thing, as the common aim is to extract meaningful information from the data. But if we look closely, they are both completely different, and machine learning is considered a subset of data science.
Who is a Data Scientist?
In 2012, data scientist was termed “the sexiest job of 21st Century” by Harvard Business School. We can define a data scientist as someone who can study and analyze data to get the past trends and also extract some information that could be helpful in the future. It involves the use of different types of statistical and predictive modern techniques. Data scientists are capable of performing tasks on data that are not only large but also unstructured.
After extracting some meaningful information from the data stack, data scientists now have the ability to make decisions that can impact a business process by finding the patterns and trends from the data.
In conclusion, a data scientist is a professional who works with both the computer world and the business sector to provide ways to improve their business process.
Who is a Machine Learning Engineer?
Unlike data scientists, machine learning engineers have a narrower set of tasks to perform. These tasks mainly focus on applying the various machine learning algorithms to a given data to make different predictions. The main task of the ML engineer is to check the working of the different algorithms and then scale them to larger data sets to obtain specific results.
A high level of programming skills is necessary for an ML engineer that can be used in different fields like speech recognition, security detection, and many more.
Job Roles and Skills Required for Data Scientist
The main and basic skill required to become a data scientist is expertise in statistical programming languages like python, R, SAS, etc. These are the primary skills required to perform different data manipulations.
A data science certification course helps in finding a good job and understanding the job responsibilities. Here are some job responsibilities of a data scientist.
- Data fetching and data storing
- Validating and optimizing business solutions
Job Roles and Skills Required for Machine Learning Engineer
A machine learning engineer should have sound knowledge of domains like robotics, speech recognition, etc. Good knowledge of programming languages like Python, R, etc., is also a prerequisite.
Some of the following tasks that ML engineers perform are:
- Performing Ml tests
- Training systems
- Providing technical knowledge
Data science is a broader term for numerous processes, and machine learning is a major part of it. Machine learning requires strong knowledge of programming skills whereas, data science requires analytical and statistical skills.