Data science and Machine Learning have helped advance many industries and can be essential components of business technology to make intelligent data-driven decisions. With data science and Machine Learning, we can weed through masses of information and processes to make the best decision in each situation. While data science and Machine Learning both involve analyzing data, they are discrete subject areas.
What Is Data Science?
Data science is used to gain insightful information from data. It is an interdisciplinary field that incorporates predictive computer science, scientific processes and methods, statistics, mathematics, and business. Its interdisciplinary nature makes it difficult to draw a clear distinction between what is and isn’t data science.
A common misconception is that artificial intelligence (AI) and data science are interchangeable terms. AI designates a model or machine that tries to mimic human behavior and produce human-like decisions. Data science methods such as deep learning are incorporated in AI but are not confined to them. Machine Learning is an important domain within data science.
The Role of Data Scientists
Data scientists use both structured and unstructured data in their analyses. Structured data can come in the form of spreadsheets or .csv files. Unstructured data might be images, video and audio files, or any other type of data.
In small companies, a data scientist might be the sole data person and might have responsibility for the entire analysis process. Companies that can afford more resources will have a greater number of data science specializations. The main activities that a data scientist can perform are data collection, data pre-processing, data organization, dashboard creation, A/B testing, statistical inference, and building and deploying ML models.
The end goal for a data scientist is to make a meaningful contribution to the business and to create value for the company. A data scientist can help a company make better, data-informed decisions when it comes to their customers and employees. For example, because of the work data scientists can provide, streaming services know which programs to recommend to the subscriber next, banks can detect fraud more easily, and utility service suppliers such as cable and Internet companies can predict when a customer is interested in switching to another provider. Data scientists add value to a business through the optimization of existing operations.
What Is Machine Learning?
Machine Learning is a technique that uses statistical methods to enable machines to learn without being specifically programmed for a task. According to Magnimind Academy, ML allows algorithms to learn from data, collect insights, and make predictions on unanalyzed data based on the gathered information.1 The three primary types of Machine Learning algorithms are supervised learning, unsupervised learning, and reinforcement learning.2
Machine Learning best occurs when a machine takes in data and learns information about the world that would be too difficult or time-consuming for humans. According to CompSuccess, ML goes beyond human capabilities by processing massive quantities of data very quickly using algorithms that change over time to get better at what they were intended to do.3 ML spots patterns and identifies anomalies that might indicate problems that humans can then address. Machine Learning is a subset of AI that falls within the "limited memory" category in which the AI (machine) can learn and develop over time.
The Role of Machine Learning Experts
Machine Learning experts, or machine learners, design and develop algorithms to discover new data predictions. Machine learners prepare and analyze historical data to identify patterns.
Machine learning is used to provide technical support for program management and business development activities, which might include proposal writing and customer development.
Data Science and Machine Learning at UMGC
¶¶ÒõÊÓƵ (UMGC) offers a skill-based curriculum based on emerging workforce and industry needs. UMGC’s data science bachelor’s degree program focuses on real-world application to give students experience and the preparation to meet the challenges of today and tomorrow in the world of data. Our multidisciplinary bachelor’s degree program in data science uses both technical and managerial skills to prepare students for business, data analytics, and computational competencies. The program culminates with capstone projects addressing real life problems from industry sponsors.
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