A rapidly growing field with a high demand for skilled professionals…
Artificial intelligence and machine learning are the future of tech. These technologies are already being used to revolutionize a wide variety of industries, from healthcare to finance to retail.
As AI and ML continue to evolve, the demand for skilled professionals in these fields will only increase. That’s why it’s so important to learn AI and ML skills now.
Here are just a few of the benefits of learning AI and ML skills:
- High salaries: AI and ML professionals can command high salaries, often earning more than other tech professionals.
- Job security: The demand for AI and ML professionals is growing rapidly, so there are plenty of job opportunities available.
- Personal satisfaction: AI and ML work can be incredibly rewarding. You’ll get to use your skills to solve real-world problems and make a difference in the world.
If you’re interested in a career in tech, or if you simply want to learn new and valuable skills, we encourage you to check and explore some AI and ML skills. It’s a great way to future-proof your career and open up new opportunities for yourself.
Spring 2024
CIS 96F: Introduction to Artificial Intelligence and Machine Learning
Lecture: 6:30pm – 8:20pm Wednesday (Online)
Lab: 8:30am – 12:20pm Saturday (In-person)
MATH 118: Foundations in Data Science
Lecture: 9am – 10:15am Monday (in person)/Wednesday (online, optional in person)
Lab: 10:30am – 11:45am Monday (in person)/Wednesday (online, optional in person)
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Frequently Asked Questions
What is artificial intelligence (AI)?
AI is a branch of computer science that deals with the creation of intelligent agents, which are systems that can reason, learn, and act autonomously. AI research has been highly successful in developing effective techniques for solving a wide range of problems, from game playing to medical diagnosis.
What is machine learning (ML)?
ML is a subset of AI that deals with the creation of systems that can learn from data. ML systems are able to improve their performance over time without being explicitly programmed. ML has been used to achieve state-of-the-art results in a wide range of applications, including image recognition, natural language processing, and fraud detection.
Which Artificial Intelligence/Machine Learning and Data Analytics courses are available at Laney College?
2023 Fall Registration is available for the following:
- MATH 118 – Foundations in Data Science: Collecting data, sampling; observational and experimental studies; tables and graphs; histograms; measures of center, spread, and correlation; probability; random variables; normal distributions; confidence intervals; hypothesis testing; Regression; ethical issues; algorithm design, flow charting, and debugging; elements of good programming style.
- CIS 96F – Introduction to Artificial Intelligence and Machine Learning: Artificial Intelligence (AI) basic concepts and Machine Learning (ML) techniques: Classification and Prediction, Natural Language Processing (NLP), Computer Vision (CV), Deep Learning (DL), AI project cycles, culture, and professional expectations.
- CIS 96L – Natural Language Processing I: Fundamental concepts in Natural Language Processing (NLP): Basic understanding of NLP and its applications, NLP models and algorithms, data sets and visualization techniques, and NLP programming tools.
- CIS 96M – Natural Language Processing II: Advanced Natural Language Processing (NLP): Forefront technologies and techniques in testing and building applications through transformers and models.
What are the future trends in AI and ML?
The future of AI and ML is very bright. These technologies are already being used to revolutionize a wide variety of industries, and the demand for AI and ML professionals is only going to increase. Some of the most promising future trends in AI and ML include:
- Deep learning: Deep learning is a type of machine learning that uses artificial neural networks to learn from data. Deep learning has been used to achieve state-of-the-art results in a wide range of applications, including image recognition, natural language processing, and fraud detection.
- Natural language processing: Natural language processing (NLP) is a field of computer science that deals with the interaction between computers and human (natural) languages. NLP is used in a wide variety of applications, including machine translation, speech recognition, and text analysis.
- Computer vision: Computer vision is a field of computer science that deals with the extraction of meaning from digital images or videos. Computer vision is used in a wide variety of applications, including self-driving cars, facial recognition, and medical image analysis.
