Artificial Intelligence Training

Artificial Intelligence Training Program is a blend of Artificial Intelligence, Data Science, Machine Learning, and Deep Learning, enabling the real-world implementation of advanced tools and models. The program is designed to give you in-depth knowledge of Artificial Intelligence concepts including the essentials of statistics required for Data Science, Python programming, and Machine Learning. Through these courses, you will learn how to use Python libraries like NumPY, SciPy, Scikit, and essential Machine Learning techniques, such as supervised and unsupervised learning, advanced concepts covering artificial neural networks and layers of data abstraction and TensorFlow.

Artificial intelligence and Machine Learning will impact all segments of daily life by 2025, with applications in a wide range of industries such as healthcare, transportation, insurance, transport and logistics, and customer service. A role in this domain places you on the path to an exciting, evolving career that is predicted to grow sharply into 2025 and beyond.

Why Become an AI Engineer?

The current and future demand is staggering. The New York Times reports candidate shortage for certified artificial intelligence training, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the U.S. (or Rs.17 lakhs to Rs. 25 lakhs in India) for engineers with the required skills.

What you’ll learn?

By the end of this Artificial Intelligence Master’s Program, you will be able to accomplish the following:

• Understand the meaning, purpose, scope, stages, applications, and effects of Artificial Intelligence
• Design and build your own intelligent agents, applying them to create practical Artificial Intelligence projects, including games, machine learning models, logic constraint satisfaction problems, knowledge-based systems, probabilistic models, and agent decision-making functions
• Master the essential concepts of Python programming, including data types, tuples, lists, dicts, basic operators, and functions
• Learn how to write your own Python scripts and perform basic hands-on data analysis using Jupyter notebook
• Gain an in-depth understanding of Data Science processes: data wrangling, data exploration, data visualization, hypothesis building, and testing
• Perform high-level mathematical and technical computing using the NumPy and SciPy packages and data analysis with the Pandas package
• Master the concepts of supervised and unsupervised learning models, including linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipeline, recommendation engine, and time series modeling
• Understand the concepts of TensorFlow, its main functions, operations, and the execution pipeline
• Master advanced topics in Artificial Intelligence, such as convolutional neural networks, recurrent neural networks, training deep networks, and high-level interfaces