5 answers
5 answers
Updated
Jenny’s Answer
Great question! AI/ML can be used in so many ways. Many companies are looking to leverage AI/ML modeling for data analytics to inform their business decisions. You can use for a job in strategy, marketing, program management, finance and more. There's so many uses for this skill set and you may want to look at in several different ways until you find the right way you want to position this skill set in the job you want. Strategy may look at AI/ML modeling to predict market trends and new growth areas. Marketing may use this for targeting and better customer insights & propensity to buy, finance may use this when creating annual operating plans and budgets. It's a great way to pull in lots of data analytics that could inform the business.
Updated
Ramesh’s Answer
Hi Melinda,
There are three broad ways you can have a career that uses AI/ML:
1) Become a developer of AI/ML technology: CS Major specializing in AI/ML, Applied Math/Statics Major specializing AI/ML, ...
2) Become a Specialist in Applied AI/ML: Data Science major - sometimes this overlaps with CS Major
3) Become an AI Specialist in a STEM centric Field: Major in Engineering/Sciences/Finance etc. with a minor in Data Science
There are three broad ways you can have a career that uses AI/ML:
1) Become a developer of AI/ML technology: CS Major specializing in AI/ML, Applied Math/Statics Major specializing AI/ML, ...
2) Become a Specialist in Applied AI/ML: Data Science major - sometimes this overlaps with CS Major
3) Become an AI Specialist in a STEM centric Field: Major in Engineering/Sciences/Finance etc. with a minor in Data Science
Updated
Ishan’s Answer
Hey Melinda,
Nowadays, so many companies out there are turning to AI/ML to help their business do well. You have definitely chosen a great path to pursue as it will only grow and get better, you will be there from the beginning. Since so many companies and industries use AI/ML, the thing that you should focus on is what vertical, i.e. industry, you think you would want to work in. I would recommend using resources such as Kaggle to enter competitions, look at projects, get inspiration, and other collaborators code to create your own projects from various industries to see what you really like. And even if you do not know by the time you graduate, that is 100% ok! You can go into a field similar to mine, tech consulting. I work with AI/ML techniques everyday for every sector and I absolutely love it because it allows me to gain a holistic knowledge about how the world operates.
Nowadays, so many companies out there are turning to AI/ML to help their business do well. You have definitely chosen a great path to pursue as it will only grow and get better, you will be there from the beginning. Since so many companies and industries use AI/ML, the thing that you should focus on is what vertical, i.e. industry, you think you would want to work in. I would recommend using resources such as Kaggle to enter competitions, look at projects, get inspiration, and other collaborators code to create your own projects from various industries to see what you really like. And even if you do not know by the time you graduate, that is 100% ok! You can go into a field similar to mine, tech consulting. I work with AI/ML techniques everyday for every sector and I absolutely love it because it allows me to gain a holistic knowledge about how the world operates.
Updated
Rodrigo’s Answer
Hi Melinda
Almost all the works with programming and ingeneering, first you have to study some engineer career, dedicated to IT , coding, software, robotics, mechatronics and then you can be specialized in AI/Machine Learning,
Almost all the works with programming and ingeneering, first you have to study some engineer career, dedicated to IT , coding, software, robotics, mechatronics and then you can be specialized in AI/Machine Learning,
Updated
Vineet’s Answer
Great question Melinda! There are lots of roles involved in building/improving AI. A few examples are:
1. Software Engineering: Build the tools that allow data scientists to train models and also deploy the models efficiently.
2. Data Scientist: Builds and improves methods for AI models themselves.
3. AI ethicists: Conduct research and write papers and recommendations on how to reduce bias (i.e. racial bias, gender bias) that machine learning models often introduce.
4. Legal teams: Define parameters of what the AI is allowed to say and not say and ensure it follows the law, including privacy rules.
5. UX writers and content writers/editors: Create the language and tone used by conversational bots (i.e. Google Assistant).
Most industries now use AI in some form and hire AI people to build and improve their AI products. Here are two examples:
1. Self-driving vehicles: For turning camera/LIDAR/Radar data into an interpretation of the world and next action for the car to take.
2. VR/AR Gaming: Translating person's movements into the movements that their avatars make.
1. Software Engineering: Build the tools that allow data scientists to train models and also deploy the models efficiently.
2. Data Scientist: Builds and improves methods for AI models themselves.
3. AI ethicists: Conduct research and write papers and recommendations on how to reduce bias (i.e. racial bias, gender bias) that machine learning models often introduce.
4. Legal teams: Define parameters of what the AI is allowed to say and not say and ensure it follows the law, including privacy rules.
5. UX writers and content writers/editors: Create the language and tone used by conversational bots (i.e. Google Assistant).
Most industries now use AI in some form and hire AI people to build and improve their AI products. Here are two examples:
1. Self-driving vehicles: For turning camera/LIDAR/Radar data into an interpretation of the world and next action for the car to take.
2. VR/AR Gaming: Translating person's movements into the movements that their avatars make.