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Artificial Intelligence Certification Training

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Reviews 4.9 (4.6k+)

Rated 4.7 out of 5

Learners : 1080

Duration : 25 Days

About Course

🌐 Artificial Intelligence (AI) Online Training

Artificial Intelligence (AI) is one of the most transformative technologies of the modern era, empowering machines to think, learn, and act intelligently. This course provides in-depth training in Artificial Intelligence concepts, machine learning, neural networks, natural language processing, and deep learning — equipping learners to design and deploy intelligent systems across industries like healthcare, finance, automation, and more.

Its Core Capabilities Include:

Artificial Intelligence Fundamentals & Concepts:
Understand the foundations of Artificial Intelligence, including agents, environments, search algorithms, and knowledge representation.
Machine Learning (ML):
Learn supervised, unsupervised, and reinforcement learning techniques using real-world data.
Deep Learning:
Master neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs) using TensorFlow and PyTorch.
Natural Language Processing (NLP):
Build applications that process and understand human language using text analysis and sentiment detection.
Computer Vision:
Develop image classification, object detection, and facial recognition systems using Artificial Intelligence frameworks.
Model Deployment & MLOps:
Deploy Artificial Intelligence and ML models in production using cloud platforms and automate workflows using MLOps principles.
Artificial Intelligence Ethics & Governance:
Understand ethical Artificial Intelligence , responsible data usage, and fairness in Artificial Intelligence model design.

📍 Bonus: Certification Tracks

Microsoft Certified: Azure Cloud Associate
Google Cloud Professional Machine Learning Engineer
IBM Applied Artificial Intelligence Professional Certificate
Artificial Intelligence Professional (Viswa Online Trainings)

Artificial Intelligence Training Course Syllabus

Deep Learning: A revolution in Artificial Intelligence

Limitations of Machine Learning

What is Deep Learning?

Need for Data Scientists
Foundation of Data Science
What is Business Intelligence
What is Data Analysis
What is Data Mining

Data

Basis of Data Categorization
Types of Data
Data Collection Types
Forms of Data & Sources
Data Quality & Changes
Data Quality Issues
Data Quality Story
What is Data Architecture
Components of Data Architecture
OLTP vs OLAP
How is Data Stored?

Big Data

Big Data Architecture
Big Data Technologies
Big Data Challenge
Big Data Requirements
Big Data Distributed Computing & Complexity
Hadoop
Map-Reduce Framework
Hadoop Ecosystem

Data Science Deep Dive

What Data Science is
Why Data Scientists are in demand
What is a Data Product
The growing need for Data Science
Large Scale Analysis Cost vs Storage
Data Science Skills
Data Science Use Cases
Data Science Project Life Cycle & Stages
Data Acquisition
Where to source data
Techniques
Evaluating input data
Data formats
Data Quantity
Data Quality
Resolution Techniques
Data Transformation
File format Conversions
Anonymization

Python

Python Overview
About Interpreted Languages
Advantages/Disadvantages of Python pydoc.
Starting Python
Interpreter PATH
Using the Interpreter
Running a Python Script
Using Variables
Keywords
Built-in Functions
StringsDifferent Literals
Math Operators and Expressions
Writing to the Screen
String Formatting
Command Line Parameters and Flow Control.
Lists
Tuples
Indexing and Slicing
Iterating through a Sequence
Functions for all Sequences

Operators and Keywords for Sequences

Range() function
List Comprehensions
Generator Expressions
Dictionaries and Sets.

Numpy & Pandas

Learning NumPy
Introduction to Pandas
Creating Data Frames
GroupingSorting
Plotting Data
Creating Functions
Slicing/Dicing Operations.

Deep Dive – Functions & Classes & Oops

Functions
Function Parameters
Global Variables
Variable Scope and Returning Values. Sorting
Alternate Keys
Lambda Functions
Sorting Collections of Collections
Classes & OOPs

Statistics

What is Statistics
Descriptive Statistics
Central Tendency Measures
The Story of Average
Dispersion Measures
Data Distributions
Central Limit Theorem
What is Sampling
Why Sampling
Sampling Methods
Inferential Statistics
What is Hypothesis testing
Confidence Level
Degrees of freedom
What is pValue
Chi-Square test
What is ANOVA
Correlation vs Regression
Uses of Correlation & Regression

Machine Learning, Deep Learning & Artificial Intelligence using Python

Introduction
ML Fundamentals
ML Common Use Cases
Understanding Supervised and Unsupervised Learning Techniques

Clustering

Similarity Metrics
Distance Measure Types: Euclidean, Cosine Measures
Creating predictive models
Understanding K-Means Clustering
Understanding TF-IDF, Cosine Similarity and their application to Vector Space Model
Case study

Implementing Association rule mining

Case study
Decision Tree Classifier
How to build Decision trees
What is Classification and its use cases?
What is Decision Tree?
Algorithm for Decision Tree Induction
Creating a Decision Tree
Confusion Matrix
Case study
Random Forest Classifier
Naive Bayes Classifier
Problem Statement and Analysis
Various approaches to solving a Data Science Problem
Pros and Cons of different approaches and algorithms.
Linear Regression
study
Introduction to Predictive Modeling
Linear Regression Overview
Simple Linear Regression
Multiple Linear Regression
Logistic Regression
Case study
Logistic Regression Overview
Data Partitioning
Univariate Analysis
Bivariate Analysis
Multicollinearity Analysis
Model Building
Model Validation
Model Performance Assessment AUC & ROC curves
Scorecard
Support Vector Machines
Case Study
Introduction to SVMs
SVM History
Vectors Overview
Decision Surfaces
Linear SVMs
The Kernel Trick
Non-Linear SVMs
The Kernel SVM
Time Series Analysis Describe Time Series data
Format your Time Series data
List the different components of Time Series data
Discuss different kind of Time Series scenarios
Choose the model according to the Time series scenario
Implement the model for forecasting
Explain working and implementation of ARIMA model
Illustrate the working and implementation of different ETS models
Forecast the data using the respective model
What is Time Series data?
Time Series variables
Different components of Time Series data
Visualize the data to identify Time Series Components
Implement ARIMA model for forecasting
Exponential smoothing models
Identifying different time series scenarios based on which different Exponential
The smoothing model can be applied
Implement respective model for forecasting
Visualizing and formatting Time Series data
Plotting decomposed Time Series data plot
Applying ARIMA and ETS model for Time Series forecasting
Forecasting for given Time period
Case Study
Machine learning algorithms Python
Various machine learning algorithms in Python
Apply machine learning algorithms in Python

Artificial Intelligence Course Key Features

Live Instructor based training with software
Certification Oriented content
Hands-on complete Realtime training
Flexible schedule demo's & classes
Live recorded videos access
Study material provided
JOB Assistance

Course completion certificate

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Artificial Intelligence Online Training FAQ'S

What is Artificial Intelligence?

AI is the simulation of human intelligence in machines that can learn, reason, and make decisions to perform tasks autonomously.

Explore Learning Resources on Pinterest

What is the difference between AI, Machine Learning, and Deep Learning?

AI is the broader concept of intelligent machines; ML is a subset that focuses on algorithms that learn from data, and Deep Learning is an ML technique based on neural networks.

What is supervised learning?

Supervised learning uses labeled data to train algorithms to predict outcomes or classify inputs.

What are neural networks?

Neural networks are computing systems inspired by the human brain, consisting of layers of interconnected nodes that process data patterns.

What are some real-world applications of AI?

AI is used in self-driving cars, recommendation systems, fraud detection, chatbots, and predictive maintenance.

Reviews

    
 
 
         
   Chandu Gutlapalli 
 
 
 
 Trustindex verifies that the original source of the review is Google. I have attended the Big data Hadoop online course In VISWA Technologies. Course content is excellent. I would recommend this course anyone wants to make the career in the analyst. instructor (Rajesh sir) describes you course in detail. All Presentations are very good. The Course Material is truly great, and Good thing is that you will get Project Explanation with Case Studies.
  
 
        
   Pudi Nithish 
 
 
 
 Trustindex verifies that the original source of the review is Google. I had a great experience with Jaya Vardhan. Very good faculty the teaching style is clear and practical and the course material is well structured and up to date. Very good lab faculty is too supportive. Overall it's very good place learn Datadog from expert trainer.
  
 
        
   Rahul Dharmapuri 
 
 
 
 Trustindex verifies that the original source of the review is Google. Good Institute
  
 
        
   Sai kiran 
 
 
 
 Trustindex verifies that the original source of the review is Google. Great institute, chaithanya sir is friendly, highly recommend for both beginner and working professionals
  
 
        
   Tharak 
 
 
 
 Trustindex verifies that the original source of the review is Google. Excellent Experience. I would Recommend others to Join this course Oracle OTM & GTM.
  
 
        
   S I V A ROCK 
 
 
 
 Trustindex verifies that the original source of the review is Google. I recently completed the Oracle 19c DBA course at VISWA Online Trainings, and it was an excellent learning experience. The trainer explained every topic clearly with real-time examples and practical sessions. The hands-on labs helped me gain confidence in database administration. I highly recommend this course to anyone who wants to build a career as an Oracle DBA.
  
 
        
   Nikil 
 
 
 
 Trustindex verifies that the original source of the review is Google. The course was very well structured. I have taken Weblogic Admin Training. My learning journey was excellent at VISWA Online Trainings!
  
 
        
   Monica Benny 
 
 
 
 Trustindex verifies that the original source of the review is Google. I recently completed the Oracle Analytics Cloud (OAC) and Fusion Data Intelligence (FDI) training program with Viswa Training, and it has been an exceptional learning experience from start to finish.

The entire journey was well-supported. Chaithanya was extremely responsive, ensuring seamless coordination and assistance throughout the learning process.

The instructor brought a high level of expertise and depth to the classroom. Their extensive knowledge of the subject matter made complex analytical concepts easy to grasp and highly applicable to real-world scenarios.

Thanks to this structured curriculum and expert instruction, I now have a robust, comprehensive understanding of Oracle Analytics Cloud technology. Highly recommended for anyone looking to upskill in enterprise analytics!

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