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Artificial Intelligence certification

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Artificial Intelligence certification

Artificial Intelligence Online Course

The Artificial Intelligence online course has been conceived by our leading industry experts as per the current industry standards to give our learners the working knowledge of A.I. Artificial intelligence (AI) is a broad field of computer science that deals with the creation of intelligent machines capable of performing tasks that normally require human intelligence.AI is an interdisciplinary science that includes a variety of approaches. It is causing a paradigm shift in almost every area of the technology industry. This A. I course online will help you master the concepts of AI programming, the application of AI. Our AI certification is in line with market requirements which will equip you with the skillset to adopt robust Artificial Intelligence systems. This Artificial Intelligence online training will make you a pro in handling all the real-time issues that may arise in organizations and businesses.

Course Overview

Artificial Intelligence helps you improve the business and the way the employees work. Learn AI online and enhance your understanding of interesting trends, facts, and insights. In this AI course, you will explore the relationship between AI and humans and the skills necessary to work with AI. Our expert trainers are always eager to solve your queries and help you identify your shortcomings by providing the best information followed in the industry.

Our live instructor-led classes are designed to give you the best learning environment with classes being much more interesting and engaging. Our AI tutorial covers all the aspects from basics to advance level. By the end of this course, you will become a pro in implementing AI and using AI effectively.

Artificial Intelligence Certification Key Features

  • Fundamentals of Artificial Intelligence
  • Implementation of Artificial intelligence systems
  • Get Artificial intelligence certification
  • Provide you with important AI interview questions
  • Real-time base scenario projects for practice
  • Schedule your timings according to your convenience


Who Should Take This Artificial Intelligence Course?

This course primarily benefits programmers, business analysts, computer engineers, system engineers, and IT professionals who looking for a change in their domain or want to upskill their existing knowledge. Freshers who want to pursue a career in the AI domain. Additionally, professionals seeking AI certification to advance their careers.

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Course curriculum / Syllabus

Introduction to Computer Science
  • What is computer science?
  • What is machine learning?
  • What is deep learning?
  • What is artificial intelligence?
  • Analysis of data and data types.
Introduction to Python
  • What is Python?
  • Why Python?
  • How to install Python
  • Python IDE
  • Overview of the Jupyter notebook
Python Basics
  • Basic Python data types
  • What are lists in Python?
  • What is splitting?
  • Use of IF operators
  • What are cycles in Python?
  • What is a dictionary and how do we use it?
  • What is the double method?
  • What are functions in Python?
  • What is an array?
  • Selecting by tags and location
Python packages
  • What is pandas and where is it used?
  • What is Numpy in Python?
  • What is scikit learn in python?
  • What is the mat plot library?
Importing Data
  • Reading CSV files in Python
  • Writing data in Python
  • Loading objects in Python
  • Writing data to a CSV file
Data Manipulation
  • Selecting rows/observations
  • Rounding numbers
  • Selecting columns/fields
  • How to combine data
  • Combining data in Python
  • Techniques for aggregating data in Python
Fundamentals of Statistics
  • Central tendency
  • What is the mean?
  • What is the median?
  • What is a country?
  • What is the slope?
  • What is the normal distribution in Pythons?
  • Probability calculation in Python
  • What does the term probability mean?
  • Types of probabilities
  • ODDS ratios ?
  • Standard deviation
  • Variation and distribution of data
  • What are Outliers?
  • Agreement on the change
  • What is underperformance?
  • What is outperformance?
  • Distance measures
  • What is Euclidean distance and how is it calculated?
  • How is the Manhattan distance calculated?
  • What is a gap analysis?
  • What is an analysis of variance?
  • Interquartile range
  • Case Diagram
  • What is the upper bound and how is it determined?
  • What is the lower limit?
  • What is a scatter plot and how is it drawn?
  • What is the distance from Cook?
  • Treatment of missing values
  • What is NA?
  • What is a centralized function in Python?
  • What is the KNN imputation method?
  • How are dummy variables created?
  • Correlation
  • What is the Pearson correlation coefficient?
  • What are positive and negative correlations?
Error Measurement
  • What measures are used in classification problems?
  • What is a mixture matrix?
  • What is a precision measure?
  • What is recall and how is it calculated?
  • What is specificity?
  • What is the F1 measure and how is it calculated?
  • What is a regression measure and how is it measured?
  • What is MSE?
  • What is RMSE?
  • What is MAPE?
Machine Learning Guided learning
  • How does linear regression work?
  • How do you solve linear equations?
  • What is a gradient?
  • What is an interrupt in Python?
  • Calculating the value of an R-square
  • Logistic Regression
  • Explain what the ODDS ratio is.
  • Probability of success
  • Probability of failure exchange
  • How ROC curves are used.
  • Understand the interaction of variables and biases.
  • Unlimited learning
  • How are K-Means calculated?
  • What is K-Means++?
  • What is hierarchical clustering?
  • Concepts with Support Vectors
  • What are support vectors?
  • What are hypergraphs in SVMs?
  • What is a two-dimensional case?
  • Use of linear hyperplanes
  • SVM
  • How does the linear SVM work?
  • What is a radial kernel?
  • What is a polynomial kernel?
  • Other machine learning algorithms
  • K - nearest neighbor
  • Naive Bayes classifier
  • Decision Tree - CART
  • Decision Tree - C50
  • Random forest
SCIENTIFIC INTEGRATION Introduction to Artificial Intelligence
  • What is the perceptron learning algorithm?
  • What is a multilayer perceptron?
  • What is a Markov decision process?
  • What is a logical agent and first order logic?
  • Application of artificial intelligence
Deep Learning Algorithms
  • CNN - convolutional neural network
  • RNN - Recurrent Neural Network
  • ANN - Res

Artificial Intelligence certification FAQ’s:

1.What is Artificial Intelligence?

AI is branch of computer science that deals with simulation of human intelligence in machines that are programmed to think like humans. Some of the examples of AI applications are natural language processing, Speech recognition, and machine vision.

2.What is the AI technology used for?

AI is the ability of machine to display human capabilities such as learning, creativity, reasoning, and planning. AI allows the technical systems to perceive their environment and solve problems to achieve specific goal.

3.How do I get AI certification?

We would provide you with AI certificate upon the completion of the course successfully. Our certificate is recognized with many leading organizations. It will be a value add to your resume. And will help you gain credibility while hiring.

4.Can I attend the AI demo session?

Yes, you can attend our AI demo session to give you confidence upon taking our course.

5.What if I miss the class?

We would provide you with recording of the session, and also provide you with eLearning material for self-study.

6.Do you provide AI job assistance?

Yes, we provide you the job assistance required and also help you to prepare for interview.

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