Overall Findings
Broad field of study.
Has been around forever.
Essential to business and government planning.
Specialty within data science.
Newer area of study.
Mimics human intelligence using algorithms.
Artificial intelligence is a collection ofalgorithmsdesigned to simulate human intelligence.
These algorithms usemachine learninganddeep learningto improve decision-making processes as they are fed more data.
Applications: AI Makes Decisions Based on Data Science
Makes predictions based on data.
Creates reports to guide human behavior.
Makes decisions based on data.
Autonomously preforms tasks usually performed by humans.
The main job of a data scientist is to generate reports to help decision-making.
AI can actually make data-driven, logical decisions for humans.
For example, self-driving vehicles use AI to navigate traffic using real-time sensor data.
AI also powers chatbots likeChatGPTandvirtual assistantslike Alexa and Siri.
Careers: Both Fields Are Growing and Changing
Rapidly changing due to advances in AI.
Other specialties include finance and database administration.
Rapidly growing with new technologies and opportunities.
Specialties include AI research, machine learning engineering, and AI architecture.
AI engineering and data science are lucrative career options with salaries in the six figures.
Both fields are projected to grow as artificial intelligence becomes crucial to everyday business operations.
AI engineers and other data scientists work closely together.
Uses Python, MATLAB, R, SAS, and SQL.
Heavily relies on AI.
Requires a general understanding of data science.
Also uses C++ and Java.
Will eventually become part of most jobs.
Aspiring data scientists require extensive training in statistics and computer programming.
Data scientists also benefit from strong writing and speaking skills to communicate their findings.
Many other professions use AI for various purposes, from data analysis to customer service.
Our article linked above goes into more detail about ChatGPT.
Using algorithms, Machine Learning takes a set of data and categorizes the data into similar types of information.
In it’s most simplistic form, an algorithm is a set of instructions.
