Artificial Intelligence Online Course:

Artificial Intelligence is the bridge between the realm of the human mind and the reality of machines and is an integration of mathematical algorithms, computational programming and psychology. It deals with creating intelligent machines that think like a human mind. Artificial intelligence has simplified human tasks and provided assistantship to complex assignments of data visualisations, visual perception, language translation, and most distinct of all, decision-making. While natural language processing enables machines to understand and generate and interpret human-like responses, in machine learning, the system is trained on large datasets and makes decisions without actually guiding it to do so.

How will Learnfly help you become better at Artificial Intelligence?

Under the guidance of experts and professionals in the domain, you will learn the different elements of artificial intelligence and data science engineering:

• what AI is and why it’s important
• Multiple ways AI can be used in journalism and content creation
• How to use algorithms to make connections, classify content, fine-tune, and process information
• What algorithms are, and how to use them to create solutions for everyday challenges.
• How to use the concept called ‘algorithmic thinking’ to create systems that address challenges by themselves with minimal human input.
• Deep dive into Machine Learning
• Work on Data Science with python
• Understand Deep Learning with Keras and TensorFlow

Course Overview:

The “Deep Dive into Artificial Intelligence – The Master Program” course is an intermediate-level course, curated exclusively for both beginners and professionals, and gain proficiency in AI fundamentals.

The course covers the basics as well as the advanced level concepts. The course contains content-based videos along with practical demonstrations, that perform and explains each step required to complete the task. This AI and ML program starts with an Introduction to Artificial Intelligence designed to help learners decode the mystery of Artificial Intelligence and its business applications. This beginner course provides an overview of AI concepts and workflows, Machine Learning, Deep Learning, and performance metrics.

By the end of the course, you will be able to learn about:

• Introduction to Artificial Intelligence
• Fundamentals of Machine Learning and Deep Learning
• Machine Learning Workflow
• Performance Metrics
• Overview of Data Science
• Overview of Data Analytics
• Statistical Analysis and Business
• Python Environment Setup and Essentials
• Mathematical Computing with Python
• Scientific Computing with Python
• Data Manipulation with Pandas
• Machine Learning with Scikit-Learn
• Natural Language Processing with Scikit Learn
• Data Visualization in Python using matplotlib
• Web Scraping with BeautifulSoup
• Python Integration with Hadoop MapReduce and Spark
• Introduction to AI and Machine Learning
• Data Preprocessing
• Supervised Learning
• Feature Engineering
• Supervised Learning Classification
• Unsupervised Learning
• Time Series Modeling
• Ensemble Learning
• Recommender Systems
• Text Mining
• Introduction to TensorFlow
• Convolutional Network
• Recurrent Neural Network
• Restricted Boltzmann Machine (RBM)
• Autoencoders

In this course we introduce artificial intelligence, beginning with a brief history of attempts to understand the mind and intelligence in philosophy, psychology, and other areas of research.

In an important sense, AI is an old science, tracing its roots back at least to Aristotle. An appreciation of this background is essential for an understanding of the issues addressed in modern research. We also present an overview of some of the important application areas in AI. Our goal in level 1 is to provide both background and motivation for the theory and applications that follow.

Later, in level 2, we’ll introduce the research tools for AI problem-solving. These include the predicate calculus presented both as a mathematical system as well as a representation language to describe the essential features of a problem. After this, you will gain an artificial intelligence certification.

What are the expected prerequisites?

• A bachelor’s degree with an average of 50% or higher marks
• Basic understanding of programming concepts and mathematics.
• The course covers the concepts from the scratch. However, basic knowledge of Python would help.

Targetted Audience:

• Candidates who are willing to learn AI from scratch
• IT professionals willing to upskill themselves in AI
• Python developers willing to upskill themselves
• Data Scientists or Machine Learning Developers willing to upskill themselves
• Artificial Intelligence Aspirants
• Machine Learning Aspirants

What you’ll learn after this course?

• Introduction to Artificial Intelligence
• Model Evaluation
• Perceptron
• Overview of Data Science
• Overview of Data Analytics
• Statistical Analysis and Business
• Python Environment Setup and Essentials
• Mathematical Computing with Python
• Scientific Computing with Python
• Data Manipulation with Pandas
• Machine Learning with Scikit-Learn
• Natural Language Processing with Scikit Learn
• Data Visualization in Python using Matplotlib
• Web Scraping with BeautifulSoup
• Python Integration with Hadoop MapReduce and Spark
• Data Preprocessing
• Supervised Learning
• Regression
• Feature Engineering
• Supervised Learning Classification
• Unsupervised Learning
• Time Series Modeling
• Ensemble Learning
• Recommender Systems
• Text Mining

How to sign-up for the course?

You need to purchase the courses offered. When you sign up, you’ll immediately have unlimited viewing of thousands of expert courses, paths to guide your learning, tools to measure your skills and hands-on resources like exercise files. There’s no limit on what you can learn and you can cancel at any time