Artificial Intelligence Online Course

Have you got bored with doing the routine things?   Do you have a zeal to learn the new technology? Are you interested in the automation of things?  Do you have a passion for making the things automated? Are willing to know the automation of things. Artificial intelligence answers to all the above questions.  Learning of Artificial  Intelligence is a simple thing nowadays. But today we can learn this  artificial Intelligence  through Artificial Intelligence Course

Artificial Intelligence Course

Today, People usually prefer to do new jobs rather than traditional jobs. And they we interested to do the things, which were new to them. And they would like to automate the regular jobs. But they don’t know how to do that.  And this Artificial Intelligence Online Training guides you in a simple and efficient manner.

Learn AI in a simple an easy manner. Moreover, many people think that Learning Artificial intelligence is a big deal.  But, it is false.  Because today you can become an expert in Artificial  Intelligence even through online. Moreover,   there is no restriction to pursue this course.  Usually, Data processing and algorithms  interested candidates can pursue this course

 Usually, we used to apply Artificial Intelligence to reduce manpower.   And the main moto of AI is to reduce the manpower and to mechanize the things.  And you can achieve this by analyzing the previous activity of the user.

The Artificial Intelligence learning course consists of following concepts  :

Here we are going to learn more Topics about Artificial Intelligence from the beginning By OnlineITGuru experts team with the support of Live project support.

OnlineITGuru provides rich quality knowledge to the students.  And the trainers were real-time experience faculty. Each trainer has a minimum 10 years of industry experience.  Additionally, after this course, OnlineITGuru provide the placements in MNC (Multi-National Companies )

Learn Artificial Intelligence Online Course

Days move very quickly. When a new application is launched into the environment, it must be visible to all the users very quickly . when it was launched we used to have some issues to a certain region/ group of people. If the same issues have been faced by the end user. He would definitely ask the support team to solve the issue happened to him/ her. In such cases, one support person cannot handle(cannot answer) to all the user at a time. In such cases, we need an automation which replaces the human work. Artificial intelligence provides the automation to solve this problem.

What is Artificial intelligence?

Artificial Intelligence (AI) is the automation of Human Intelligence process by machines. These processes include the learning, reasoning, and self-correction. It emphasizes the creation of intelligent machines that work and react like humans. Today this artificial intelligence plays a major role in the IT industry.

The core of Artificial intelligence include programming computers includes the following :

Knowledge

Reasoning

Problem-solving

Perception

Learning

Planning

Ability to manipulate and move objects.

Through this course, you will be getting the knowledge of all those concepts and application of each of each in detail through Artificial Intelligence Online Training.

Who Can Take This Course?

There is no restriction for the people to take this course. Anyone who interested in automation. And who was willing to make the things in an innovative way can do this course

What are the Prerequisites?

There are nothing much prerequisites required to learn this course. It’s good to have a basic knowledge of algorithm functioning and good analyzing capabilities. But not mandatory. OnlineITGuru trainers start with all the essential basics required to pursue this course.

Benefits of OnlineITGuru

Today  Artificial Intelligence is being provided by many institutes online. But one advantage of taking the course from OnlineITGuru is that, you will get a self-placed video of your interesting technology from the available set of courses.

OnlineITGuru is providing the ethical hacking course by the real-time industry. Trainers were very skilled people who were currently working in the industry with least experience of 10 years. Along with training trainer will guide you some tips along with the useful material. This helps in clearing the certification.


Course Features

Course Duration 30 Hrs Course Duration : 30 Hrs

Highly interactive, reliable and quality learning sessions of the course are conducted by Online IT Guru. For a better learning experience, the courses are divided into distinctive phases and sessions.

Hands on Experience Hands on Experience

Every module shall be followed by a practical experience of lab exercises. At the end of the course, the students will have to build a project on the concepts that were taught to them during the course duration.

Access Duration Lifetime Access Duration: Lifetime

Students will have a life time access to the course materials provided by OnlineITGuru. Students also have an opportunity to decide the duration of the course as per their schedule and convenience.

24 X 7 Support 24 X 7 Support

Concerned faculty can be contacted by the students if they are looking for help and assistance with respect to the course and its material. Students can approach their respective faculty to clear their quires either by email, phone or through live chat.

Get Certified Get Certified

At the end of the course, students will have to fare well in quizzes and testes conducted by the institute and the faculty in order to receive the required certification. To clear the Certification test with flying colors, students will be given model questions and certification dumps that would make them confident about attempting the test to get their Certification.

Job Assistance Job Assistance

Online IT Guru will help students find job opportunities with the newly acquired skill set. Online IT Guru has a varied bunch of Clientele around the globe, over 30+ companies in USA and India that have experience in working with different technologies. We would pass your resumes to them after the completion of the course and ensure that the students achieve 100% placements. During the testing and interview process for them, the required assistance shall be provided by Online IT Guru.

Artificial Intelligence Course Content

 DATA SCIENCE

INTRODUCTION TO DATA SCIENCE

  • What is data Science? – Introduction
  • Importance of Data Science
  • Demand for Data Science Professional
  • Life cycle of data science
  • Tools and Technologies used in data Science
  • Business Intelligence vs Data Science vs Data Engineer
  • Role of a data scientist

PART A – INTRODUCTION TO STATISTICS

  1. Fundamentals of Math and Probability
  • Basic understanding of linear algebra, Matrices, vectors
  • Basics of Calculus
  • Various types and functions of matrices
  • Eigen vectors and Eigenvalues of a Matrix
  • Fundamentals of Probability
  • Types of events in Probability
  • Permutations & Combinations
  • Associative, Commutative and Distributive Laws
  1. Descriptive Statistics
  • Describe or summaries a set of data Measure of central tendency and measure of dispersion.
  • The mean, median, mode, Standard deviation, Variance, Range, kurtosis and skewness.
  • Histograms, Bar chart, Box plot
  1. Inferential Statistics
  • What is inferential statistics Different types of Sampling techniques
  • Random variable
  • Probability Distribution and Cumulative Probability Distribution
  • Binomial Distribution & Quincunx
  • Normal Distribution & Normal variable
  • Sample Vs Population summary metrics
  • Point estimate and Interval estimate
  • Creating confidence interval for population parameter using Z* score and confidence level percentage
  • Bias & Variance trade-offs
  1. Hypothesis Testing
  • Hypothesis Testing Basics
  • Null Hypothesis
  • Alternate Hypothesis
  • p-Value
  • False Positive & False Negative
  • Types of errors-Type 1 Errors, Type 2 Errors P value method, Z score Method
  • T-Test, Analysis of variance(ANOVA)
  1. Exploratory Data Analysis
  • Introduction to EDA
  • Data Sourcing & Data cleaning
  • Fixing rows, columns
  • Missing values treatment and invalid values
  • Standardize values and filter data
  • Outliers treatment
  • Types of variables
  • Univariate Analysis on Unordered, ordered and quantitative variables
  • Rank-Frequency and Power Law distribution
  • Bivariate Analysis
  • Correlation
  • Various types of Derived metrics

PART B – UNDERSTANDING AND IMPLEMENTING

MACHINE LEARNING

  1. Introduction to Machine Learning
  • What is Machine Learning?
  • Introduction to Supervised Learning, Unsupervised Learning & Semi-supervised Learning
  • What is Reinforcement Learning?
  • Variable Identification
  • CRISP-DM framework
  1. Linear Regression
  • Introduction to Linear Regression and simple linear regression
  • Cost function, R-Square, RMSE and best fit line
  • Closed form and Gradient descent
  • Linear Regression with Multiple Variables
  • Disadvantage of Linear Models Interpretation of Model Outputs Understanding
  • Multi-collinearity
  • Adjusted R-Square, P-Value and VIF
  • Missing values & Outlier treatment
  • Understanding Heteroscedasticity
  • Signature of overfitting
  • Case Study
  • Application of Linear Regression for CTG data
  1. Logistic Regression
  • Introduction to Logistic Regression
  • Binary Logistic Regression
  • Sigmoid function & Log of odds
  • Threshold Value
  • Multinomial Logistic Regression
  • Introduce the notion of classification Cost function for logistic regression
  • Application of logistic regression to multi-class classification.
  • Confusion Matrix, ROC Curve
  • AIC & BIC
  • Advantages and Disadvantages of Logistic Regression
  1. Decision Trees & Random Forest
  • Decision Tree – C4.5, CART
  • How to build decision tree? Understanding CART Model Classification Rules
  • Overfitting Problem Stopping Criteria And Pruning
  • Under fitting
  • Gini Index
  • Entropy & Information Gain
  • MDS
  • How to find final size of Trees? Model A decision Tree.
  • Introduction to Random Forests
  • Ensembles & Bagging technique
  • Out of Bag error
  • Advantages of Random Forest over Decision Trees
  1. Support Vector Machines
  • Introduction to SVM
  • Hyperplane & Linear discriminator
  • Maximal Marginal Hyperplane & Support vectors
  • Support Vector classifier
  • Slack variable
  • Boundary & Feature transformation
  • Kernel Trick
  • Handling non-linearity in the dataset using various Kernels
  • Case Study
  • 1 Business Case Study with Cardio to co-graphic data
  1. Unsupervised Learning
  • Feature Selection & Feature Extraction
  • Feature Construction
  • Hierarchical Clustering
  • K-Means algorithm for clustering – groupings of unlabeled data points.
  • Principal Component Analysis(PCA)
  • Association Rules
  • Case Study
  • Market Basket Analysis
  • Dimensionality reduction on CTG

PART C – PYTHON PROGRAMMING

  1. Python Introduction
  • Python background, features
  • Installation and Various Python IDEs
  • Python vs Other languages
  1. Basics
  • Operators in Python – Arithmetic, Relational, Logical and Assignment Operators
  • Variables, Types Of Variables
  • Naming conventions
  • String operations
  1. Data Structures
  • Lists
  • Tuples
  • Sets
  • Dictionaries
  • Comprehensions
  1. Python for Data Science
  • Numerical Python
  1. ND array
  2. Subset, slicing
  3. Indexing
  4. List vs ND array
  5. Manipulating arrays
  6. Mathematical operations and apply functions
  7. Linear algebra operations
  • Pandas
  1. Data loading
  2. Series and Data frame
  3. Selecting rows and columns
  4. Position and label-based indexing
  5. Slicing and dicing
  6. Merging and concatenating
  7. Grouping and summarizing
  8. Lambda functions and pivot tables
  9. Data Processing, cleaning
  10. Missing Values
  11. Outliers
  • Data visualization
  1. Introduction to Matplotlib

Basic plotting

Figures and sub plotting

Box plot, Histograms, Scatter plots, image loading

  1. Introduction to Sea born

Histogram, rugged plot, hex plot and density plot

Joint plot, pair plot, count plot, Heat maps

  1. Plotting categorical data and aggregation of values
  2. Plotting Time-Series data using tsplot

BIG DATA

  1. Understanding Big Data and Hadoop
  • What is Data?
  • Different types of Data
  • What is Big Data and the purpose? Where dowe use it?
  • Various Big Data technologies Why Hadoop?
  • Hadoop Eco system Rack awareness
  1. HDFS Architecture
  • Hadoop 1.xvs 2.x
  • HDFS Cluster architecture
  • Resource management and configuration files
  • Slaves and master
  • Data loading techniques
  1. Map Reduce
  • MapReduce Paradigm
  • Advantages of MapReduce
  • Architecture and various components of Map Reduce
  • YARN and workflow
  • Data orchestration in Map Reduce job flow
  • Combiners, Practitioners
  1. Advanced Map Reduce
  • Joins
  • Various Data Types
  • Input formats
  • Output formats
  • MRUnit testing framework
  • Counters
  • Distributed Cache
  • Sequence File
  1. Pig
  • What is Pig and why is it required?
  • Pig vs MapReduce
  • Pig components and structure
  • Data Types
  • Data structures
  • Pig limitations
  • Pig Latin
    • Operators
    • Functions
  1. Hive
  • What is Hive and where to use
  • Pig Vs Hive
  • Hive architecture and components
  • Data Types and data models
  • Partitions, buckets
  • Data loading
  • Hive QL
    • UDF
    • Index
    • Views
    • Joins
    • Partitioning
  1. H Base       
  • Introduction to No SQL Database
  • H Base storage architecture
  • H Base components
    • Regions
    • Client
    • Modes
    • Ports and utilities
  • Attributes
  • Data Model
  • Data Loading
  • H Base API
  • Zookeeper and H Base
  1. Sqoop and Flume
  • Understand Data Ingestion
  • Introduction to Sqoop and Flume
  • Sqoop: Import from RDBMS to HDFS
  • Sqoop: Import from RDBMS to Hive
  • Sqoop Jobs
  • Flume architecture
  • Flume agent
  • Flume sinks
  • Flume channels
  • Executing the commands
  • Flume multi agent
  1. Kafka
  • Introduction to Kafka
  • Kafka Producer
  • Kafka Consumer
  • Internals
  • Cluster membership and controller
  • Replication
  • Request processing
  • Data Storage
  • File processing
  • Compaction
  • Broker
  • Cluster architecture
  • Monitoring
  1. Oozie
  • Overview
  • Workflow
  • Scheduling in Oozie
  • Configuration files
  • Monitoring and Coordinator
  • Time and Data triggers
  • Oozie console
  1. Spark
  • Spark Overview and architecture
  • Spark Shell
  • Spark context
  • RDDs (Resilient Distributed Datasets) RDD
  • Operations
  • Partitioning
  • Transformations Actions
  • Key-value pair
  • Persistence
  • Spark streaming
  • Spark DStreams
  • Transformations
  • Request count
  • Spark SQL
  • Structured data processing
  • Spark with JSON & XML
  • Data frame operations
  • Working with CSV files & JDBC
  • Broadcast Variables
  • Accumulators
  • MapReduce vs Spark
  1. Scala
  • Overview and background
  • Scala vs other languages
  • Environment setup
  • Scala compiler
  • Immutability
  • Variables and Various operators
  • Conditional statements and Loops
  • Lists, Tuples, Maps and options
  • Comprehensions
  • Functional programming in Scala
  • Object Oriented Programming

Real Time Project Resume Preparation Tips

Interview Guidance and Support

 
Do we offer any discount on the course?

We offer Group Batch, Referral, Project, and One to One Training Discounts. If you enrolled for any course, you can take any other self-paced course as Free. Therefore, at the same time, you can learn two technologies.

Can we schedule the training based upon your availability?

You can schedule your training in all Time Zones. If you want, we offer training with US, UK, Australia, Europe Instructors in Weekends and Weekdays.

Who will provide the environment to execute the Practicals?

Our Instructor will Provide, server access to the Course aspirants. And hands-on practical training that everything you need for understanding the total course with Projects.

What is the qualification of our trainer?

Our Trainer is a certified consultant, at present he working with this technology projects and has significant experience.

Do we offer placements to the course seekers?

For Every technology, We have Job Placement Teams in India, USA and around the world. After your enrollment, we start Your resume preparation and train you to clear the certifications and Projects required for getting Job. Meanwhile, our Instructors will conduct Interview sessions and assign you projects. We forward your resumes to companies that we tie-up. We make you to get complete experience so that you get a Job.

Will OnlineITGuru help you in getting certified?

We Provide Assistance is Getting Certification. We promise you that after our training, you will definitely get certified in Respected Technology.

Do we accept the course fees in installments?

Yes, we accept Training payment in Two to three Installments, with respect to the mode of training you take.

What are the Live Projects that we provide?

Our Instructor Explains Every Topic and Project on the Software itself with real time examples. Every training Batch is considered as a software team and a project is assigned to them, after completing this project. The training will be completed. So that the Students feel the real time IT Company Environment During the Sessions, where our Instructor is like a Team Lead.

  1. HIgh quality training

    This the best place for learning  AI. This because , the trainer has initially start with the basics like python, data structure and then moved into the actual subjects. Thanks to trainer.

    avatar

    Vignesh

  2. Best training at low cost

    Today many institutes charge much for AI course. They do charge separately for Python, separately for R. But OnlineITGuru provides all these under one course at low cost. Thanks to the team !!!!

    avatar

    Soumya Reddy

  3. Good support team

    When compared to other Artificial Intelligence training institutes in  Hyderabad, OnlineITGuru has good support team. they initially given me the pre-recorded videos of initial required technologies like python, R programming

    avatar

    Shravan kumar

  4. Real time trainer

    The trainer of OnlineITGuru is an experienced candidate. And he has a  good command over the subject. His teaching helped me at low a lot in taking the considerations of the problem. Thanks to OnlineITGuru.

    avatar

    Monika sri

  5. Best training

    I recommended this institute to learn Artificial Intelligence form the scratch. Because, the trainer would cover all the topics step by step that is required to solve the problem. Thanks to OnlineITGuru for selecting the best trainers.

    avatar

    Asif khan

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