Overview of Artificial Intelligence Course in New York City

New York City is a global hub for innovation, technology and commerce. It is home to some of the best universities and cutting-edge startups in the world. With the growing role of Artificial Intelligence (AI) in various industries, there is a growing demand for AI professionals who can help businesses leverage AI to drive growth and efficiency. If you are looking for an AI course in New York City, you have plenty of great options. One of the best AI courses in New York City is offered by Columbia University’s School of Engineering and Applied Science. The program has a rigorous and comprehensive curriculum which covers the entire spectrum of AI topics such as machine learning, natural language processing, computer vision, and robotics. The program is designed to equip students with a deep understanding of AI theory as well as the practical skills needed to build AI applications. Another great option is the NYU Tandon School of Engineering’s master's in data science program with a concentration in Artificial Intelligence. The program provides a rigorous technical education in machine learning, statistical modeling, data engineering, and deep learning. The AI concentration allows students to specialize in advanced topics such as reinforcement learning, generative models, computer vision, and natural language processing. The program also emphasizes the importance of ethical and responsible AI development, ensuring graduates are equipped to handle the challenges of a rapidly evolving field. If you are looking for a more hands-on program, the Flatiron School has a comprehensive Data Science program that includes an AI and machine learning module. The program covers essential topics such as probability, statistics, data manipulation, and exploratory data analysis, before diving into more advanced AI and machine learning topics. Students learn how to build predictive models, work with deep learning libraries such as TensorFlow and Keras, and deploy machine learning models on cloud platforms. The program also includes career coaching and job search support to help students land their desired AI roles. For professionals who want to upskill in AI but do not have the time for a full-time program, there are many part-time AI courses in New York City. One such course is offered by General Assembly, a popular provider of coding boot camps and tech courses. Their part-time course covers AI and machine learning concepts in a practical and accessible manner. Students learn how to build AI models using Python and popular machine learning libraries like scikit-learn and TensorFlow. The course is delivered through online workshops, assignments, and projects, making it a flexible option for busy professionals. In conclusion, there is no shortage of great AI courses in New York City. Whether you are looking for a rigorous academic program or a practical coding boot camp, there is a course that fits your needs. With the demand for AI professionals continuing to grow, investing in an AI education is a wise career move that will open up exciting opportunities in the future.

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₹70

₹9

Skill Level

Beginner

Internship

Yes

Live Project

2

Certificate

Yes

Live Training

Yes

Career Assistance

Yes

Expiry Period

1 Months
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Artificial Intelligence Tools Covered

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Why Choose SKILLFLOOR for Artificial Intelligence in New York City?

Why Course Training in Skillfloor

Syllabus

- Overview of AI and ML

- Types of Machine Learning

- Data Collection and Preprocessing

- Basic Statistics for AI

- Python Essentials for AI

- Regression Analysis

- Classification Algorithms

- Ensemble Methods

- Model Evaluation Techniques

- Feature Engineering and Selection

- Introduction to Clustering

- Dimensionality Reduction Techniques

- Association Rule Learning

- Anomaly Detection

- Self-Organizing Maps (SOM)

- Introduction to Neural Networks

- Deep Neural Networks (DNNs)

- Convolutional Neural Networks (CNNs)

- Recurrent Neural Networks (RNNs)

- Autoencoders and Generative Models

- Introduction to NLP and Text Processing

- Text Classification and Sentiment Analysis

- Advanced NLP Techniques

- Deep Learning in NLP

- Speech Recognition and Processing

- Introduction to Computer Vision

- Image Classification with CNNs

- Object Detection Techniques

- Image Segmentation

- Video Processing and Analysis

- Introduction to Reinforcement Learning

- Markov Decision Processes (MDP)

- Q-Learning and SARSA

- Deep Q Networks (DQN)

- Applications of Reinforcement Learning

- Ethical Implications of AI

- Fairness and Bias in AI

- Privacy and Security Concerns

- Explainability in AI

- Legal and Regulatory Aspects

- AI in Healthcare

- AI in Finance

- AI in Manufacturing

- AI in Retail

- AI in Autonomous Systems

- Defining and Planning a Capstone Project

- Data Preparation for Projects

- Model Building and Testing

- Model Deployment Techniques

- Project Presentation and Evaluation

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