Data science is a field that studies data and how to extract meaning from it, using a series of methods, algorithms, systems, and tools to extract insights from structured and unstructured and unstructured data.
That knowledge then gets applied to business, government, and other bodies to help drive profits, innovate products and services and public systems, and more.
Machine Learning
Machine Learning is a branch of artificial intelligence that uses algorithms to extract data and then predict future trends. Software is programmed with models that allow engineers to conduct statistical patterns In the data.
Data scientists often incorporate machine learning in their work where appropriate, to help gather more information faster or to assist with trends analysis.
Skills Needed
Data Science
Strong knowledge of programming languages like Python, R, SAS, and more.
Familiarity working with large amount of structure and unstructured data.
Comfortable with processing and analyzing data for business needs.
Understanding of math, statistics, and probability.
Data visualization and data wrangling skills.
Knowledge of machine learning algorithms and models.
Good communication and teamwork skills.
Machine Learning
Expertise in computer science, including data structures, algorithms, and architecture.
Strong understanding of statistics and probability.
Knowledge of software engineering and systems design.
Programming knowledge, such as Python, R and more.
Ability to conduct data modelling and analysis.
Careers
Data Science
Data Scientist: uses data to understand and explain the phenomena around them, to help organizations make better decisions.
Data analyst: gathers, cleans, and studies data sets to help solve business problems.
Data engineer: build systems that collect, manage, and transform raw data into information for business analysts and data scientists.
Data architect: Reviews and analyses an organization’s data infrastructure to plan databases and implement solutions to store and manage data.
Business intelligence analyst: gathers, cleans, and analyses sales and customer data, interprets it, and shares findings with business teams.
Machine Learning
Machine learning engineer: researches, builds, and designs the AI responsible for machine learning, and maintaining or improving AI systems.
AI engineer: build AI development and production infrastructure, and then implement it.
Cloud engineer: Builds and maintain cloud infrastructure.
Computational linguist: develop and design computers and deal with how human language works.
Human-centered AI systems designer: design, develop, and deploy systems that can learn and adapt with humans to improve systems and society.