ARTIFICIAL INTELLIGENCE CERTIFICATION AUTHORITIES

Artificial Intelligence Course Features

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ARTIFICIAL INTELLIGENCE COURSE FEE IN BANGALORE

Live Virtual

Instructor Led Live Online

154,000
101,745

  • IABAC® & DMC Certification
  • 9-Month | 780 Learning Hours
  • 100-Hour Live Online Training
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

92,000
60,795

  • Self Learning + Live Mentoring
  • IABAC® & DMC Certification
  • 1 Year Access To Elearning
  • 10 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Learner assistance and support

Classroom

In - Person Classroom Training

154,000
116,445

  • IABAC® & DMC Certification
  • 9-Month | 780 Learning Hours
  • 100-Hour Classroom Sessions
  • 10 Capstone & 1 Client Project
  • Cloud Lab Access
  • Internship + Job Assistance

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UPCOMING ARTIFICIAL INTELLIGENCE ONLINE CLASSES IN BANGALORE

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BEST ARTIFICIAL INTELLIGENCE CERTIFICATIONS

The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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WHY DATAMITES INSTITUTE FOR ARTIFICIAL INTELLIGENCE ONLINE COURSE

Why DataMites Infographic

SYLLABUS OF AI COURSE IN BANGALORE

MODULE 1 : DATA SCIENCE COURSE INTRODUCTION 

  • CDS Course Introduction
  • 3 Phase Learning
  • Learning Resources
  • Assessments & Certification Exams
  • DataMites Mobile App
  • Support Channels

MODULE 2 : DATA SCIENCE ESSENTIALS 

  • Introduction to Data Science
  • Evolution of Data Science
  • Data Science Terminologies
  • Data Science vs AI/Machine Learning
  • Data Science vs Analytics

MODULE3 : DATA SCIENCE DEMO 

  • Business Requirement: Use Case
  • Data Preparation
  • Machine learning Model building
  • Prediction with ML model
  • Delivering Business Value

MODULE 4 : ANALYTICS CLASSIFICATION 

  • Types of Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics

MODULE 5 : DATA SCIENCE AND RELATED FIELDS 

  • Introduction to AI
  • Introduction to Computer Vision
  • Introduction to Natural Language Processing
  • Introduction to Reinforcement Learning
  • Introduction to GAN
  • Introduction to  Generative Passive Models

MODULE 6 : DATA SCIENCE ROLES & WORKFLOW

  • Data Science Project workflow
  • Roles: Data Engineer, Data Scientist, ML Engineer and MLOps Engineer
  • Data Science Project stages

MODULE 7 : MACHINE LEARNING INTRODUCTION

  • What Is ML? ML Vs AI
  • ML Workflow, Popular ML Algorithms
  • Clustering, Classification And Regression
  • Supervised Vs Unsupervised

MODULE 8 : DATA SCIENCE INDUSTRY APPLICATIONS 

  • Data Science in Finance and Banking
  • Data Science in Retail
  • Data Science in Health Care
  • Data Science in Logistics and Supply Chain
  • Data Science in Technology Industry
  • Data Science in Manufacturing
  • Data Science in Agriculture

MODULE 1 : PYTHON BASICS 

  • Introduction of python
  • Installation of Python and IDE
  • Python objects
  • Python basic data types
  • Number & Booleans, strings
  • Arithmetic Operators
  • Comparison Operators
  • Assignment Operators
  • Operator’s precedence and associativity

MODULE 2 : PYTHON CONTROL STATEMENTS 

  • IF Conditional statement
  • IF-ELSE
  • NESTED IF
  • Python Loops basics
  • WHILE Statement
  • FOR statements
  • BREAK and CONTINUE statements

MODULE 3 : PYTHON DATA STRUCTURES 

  • Basic data structure in python
  • String object basics and inbuilt methods
  • List: Object, methods, comprehensions
  • Tuple: Object, methods, comprehensions
  • Sets: Object, methods, comprehensions
  • Dictionary: Object, methods, comprehensions

MODULE 4 : PYTHON FUNCTIONS 

  • Functions basics
  • Function Parameter passing
  • Iterators
  • Generator functions
  • Lambda functions
  • Map, reduce, filter functions

MODULE 5 : PYTHON NUMPY PACKAGE 

  • NumPy Introduction
  • Array – Data Structure
  • Core Numpy functions
  • Matrix Operations

MODULE 6 : PYTHON PANDAS PACKAGE 

  • Pandas functions
  • Data Frame and Series – Data Structure
  • Data munging with Pandas
  • Imputation and outlier analysis

MODULE 1 : OVERVIEW OF STATISTICS 

  • Descriptive And Inferential Statistics
  • Basic Terms Of Statistics
  • Types Of Data

MODULE 2 : HARNESSING DATA 

  • Random Sampling
  • Sampling With Replacement And Without Replacement
  • Cochran's  Minimum Sample Size
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Biased Random Sampling Methods
  • Sampling Error
  • Methods Of Collecting Data

MODULE 3 : EXPLORATORY DATA ANALYSIS 

  • Exploratory Data Analysis Introduction
  • Measures Of Central Tendencies: Mean, Median And Mode
  • Measures Of Central Tendencies: Range, Variance And Standard Deviation
  • Data Distribution Plot: Histogram
  • Normal Distribution
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Confidence Interval
  • Parametric Hypothesis Testing Methods
  • Hypothesis Testing Errors : Type I And Type Ii
  • One Sample T-test
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test

MODULE 5 : CORRELATION AND REGRESSION 

  • Correlation Introduction
  • Direct/Positive Correlation
  • Indirect/Negative Correlation
  • Regression
  • Choosing Right Method

MODULE 1: MACHINE LEARNING INTRODUCTION 

  • What Is ML? ML Vs AI
  • ML Workflow, Popular ML Algorithms
  • Clustering, Classification And Regression
  • Supervised Vs Unsupervised

MODULE 2: PYTHON NUMPY & PANDAS PACKAGE 

  • NumPy & Pandas functions
  • Array – Data Structure
  • Core Numpy functions
  • Matrix Operations
  • Data Frame and Series – Data Structure
  • Data munging with Pandas
  • Imputation and outlier analysis

MODULE 3: VISUALIZATION WITH PYTHON 

  • Visualization Packages (Matplotlib)
  • Components Of A Plot, Sub-Plots
  • Basic Plots: Line, Bar, Pie, Scatter
  • Advanced Python Data Visualizations

MODULE 4: ML ALGO: LINEAR REGRESSSION 

  • Introduction to Linear Regression
  • How it works: Regression and Best Fit Line
  • Modeling and Evaluation in Python

MODULE 5: ML ALGO: KNN 

  • Introduction to KNN
  • How It Works: Nearest Neighbor Concept
  • Modeling and Evaluation in Python

MODULE 6: ML ALGO: LOGISTIC REGRESSION 

  • Introduction to Logistic Regression
  • How it works: Classification & Sigmoid Curve
  • Modeling and Evaluation in Python

MODULE 7: PRINCIPLE COMPONENT ANALYSIS (PCA) 

  • Building Blocks Of PCA
  • How it works: Finding Principal Components
  • Modeling PCA in Python

MODULE 8: ML ALGO: K MEANS CLUSTERING 

  • Understanding Clustering (Unsupervised)
  • K Means Algorithm
  • How it works : K Means theory
  • Modeling in Python

MODULE 1: MACHINE LEARNING INTRODUCTION 

  • What Is ML? ML Vs AI
  • ML Workflow, Popular ML Algorithms
  • Clustering, Classification And Regression
  • Supervised Vs Unsupervised

MODULE 2: ML ALGO: LINEAR REGRESSION 

  • Introduction to Linear Regression
  • How it works: Regression and Best Fit Line
  • Modeling and Evaluation in Python

MODULE 3: ML ALGO: LOGISTIC REGRESSION 

  • Introduction to Logistic Regression
  • How it works: Classification & Sigmoid Curve
  • Modeling and Evaluation in Python

MODULE 4: ML ALGO: KNN 

  • Introduction to KNN
  • How It Works: Nearest Neighbor Concept
  • Modeling and Evaluation in Python

MODULE 5: ML ALGO: K MEANS CLUSTERING 

  • Understanding Clustering (Unsupervised)
  • K Means Algorithm
  • How it works: K Means theory
  • Modeling in Python

MODULE 6: PRINCIPLE COMPONENT ANALYSIS (PCA) 

  • Building Blocks Of PCA
  • How it works: Finding Principal Components
  • Modeling PCA in Python

MODULE 7: ML ALGO: DECISION TREE 

  • Random Forest Ensemble technique
  • How it works: Bagging Theory
  • Modeling and Evaluation in Python

MODULE 8 : ML ALGO: NAÏVE BAYES 

  • Introduction to Naive Bayes
  • How it works: Bayes' Theorem
  • Naive Bayes For Text Classification
  • Modeling and Evaluation in Python

MODULE 9: GRADIENT BOOSTING, XGBOOST 

  • Introduction to Boosting and XGBoost
  • How it works: weak learners' concept
  • Modeling and Evaluation of in Python

MODULE 10: ML ALGO: SUPPORT VECTOR MACHINE  (SVM) 

  • Introduction to SVM
  • How It Works: SVM Concept, Kernel Trick
  • Modeling and Evaluation of SVM in Python

MODULE 11: ARTIFICIAL NEURAL NETWORK (ANN) 

  • Introduction to ANN
  • How It Works: Back prop, Gradient Descent
  • Modeling and Evaluation of ANN in Python

MODULE 12: ADVANCED ML CONCEPTS 

  • Adv Metrics (Roc_Auc, R2, Precision, Recall)
  • K-Fold Cross validation
  • Grid And Randomized Search CV In Sklearn
  • Imbalanced Data Set : Smote Technique
  • Feature Selection Techniques

MODULE 1: TIME SERIES FORECASTING - ARIMA 

  • What is Time Series?
  • Trend, Seasonality, cyclical and random
  • Autoregressive Model (AR)
  • Moving Average Model (MA)
  • Stationarity of Time Series
  • ARIMA Model
  • Autocorrelation and AIC 

MODULE 2: FEATURE ENGINEERING 

  • Introduction to Features Engineering
  • Transforming Predictors
  • Feature Selection methods
  • Backward elimination technique
  • Feature importance from ML modeling

MODULE 3: SENTIMENT ANALYSIS 

  • Introduction to Sentiment Analysis
  • Python packages: TextBlob, NLTK
  • Case study: Twitter Live Sentiment Analysis

MODULE 4: REGULAR EXPRESSIONS WITH PYTHON 

  • Regex Introduction
  • Regex codes
  • Text extraction with Python Regex

MODULE 5: ML MODEL DEPLOYMENT WITH FLASK 

  • Introduction to Flask
  • URL and App routing
  • Flask application – ML Model deployment

MODULE 6: ADVANCED DATA ANALYSIS WITH MS EXCEL 

  • MS Excel core Functions • Pivot Table
  • Advanced Functions (VLOOKUP, INDIRECT..)
  • Linear Regression with EXCEL
  • Goal Seek Analysis
  • Data Table
  • Solving Data Equation with EXCEL
  • Monte Carlo Simulation with MS EXCEL

MODULE 7: AWS CLOUD FOR DATA SCIENCE

  • Introduction of cloud
  • Difference between GCC, Azure,AWS
  • AWS Service ( EC2 and S3 service)
  • AWS Service (AMI), AWS Service (RDS)
  • AWS Service (IAM), AWS (Athena service)
  • AWS (EMR), AWS, AWS (Redshift)
  • ML Modeling with AWS Sage Maker 

MODULE 8: AZURE FOR DATA SCIENCE 

  • Introduction to AZURE ML studio
  • Data Pipeline and ML modeling with Azure
  • MODULE 1: DATABASE INTRODUCTION 

    • DATABASE Overview
    • Key concepts of database management
    • CRUD Operations
    • Relational Database Management System
    • RDBMS vs No-SQL (Document DB)

    MODULE 2: SQL BASICS 

    • Introduction to Databases
    • Introduction to SQL
    • SQL Commands
    • MY SQL  workbench installation
    • Comments • import and export dataset

    MODULE 3: DATA TYPES AND CONSTRAINTS 

    • Numeric, Character, date time data type
    • Primary key, Foreign key, Not null
    • Unique, Check, default, Auto increment

    MODULE 4: DATABASES AND TABLES (MySQL) 

    • Create database
    • Delete database
    • Show and use databases
    • Create table, Rename table
    • Delete table, Delete  table records
    • Create new table from existing data types
    • Insert into, Update records
    • Alter table

    MODULE 5: SQL JOINS 

    • Inner join
    • Outer join
    • Left join
    • Right join
    • Cross join
    • Self join

    MODULE 6: SQL COMMANDS AND CLAUSES 

    • Select, Select distinct
    • Aliases, Where clause
    • Relational operators, Logical
    • Between, Order by, In
    • Like, Limit, null/not null, group by
    • Having, Sub queries

    MODULE 7: DOCUMENT DB/NO-SQL DB 

    • Introduction of Document DB
    • Document DB vs SQL DB
    • Popular Document DBs
    • MongoDB basics
    • Data format and Key methods
    • MongoDB data management

MODULE 1: GIT  INTRODUCTION 

  • Purpose of Version Control
  • Popular Version control tools
  • Git Distribution Version Control
  • Terminologies
  • Git Workflow
  • Git Architecture

MODULE 2: GIT REPOSITORY and GitHub 

  • Git Repo Introduction
  • Create New Repo with Init command
  • Copying existing repo
  • Git user and remote node
  • Git Status and rebase
  • Review Repo History
  • GitHub Cloud Remote Repo

MODULE 3: COMMITS, PULL, FETCH AND PUSH 

  • Code commits
  • Pull, Fetch and conflicts resolution
  • Pushing to Remote Repo

MODULE 4: TAGGING, BRANCHING AND MERGING 

  • Organize code with branches
  • Checkout branch
  • Merge branches

MODULE 5: UNDOING CHANGES 

  • Editing Commits
  • Commit command Amend flag
  • Git reset and revert

MODULE 6: GIT WITH GITHUB AND BITBUCKET 

  • Creating GitHub Account
  • Local and Remote Repo
  • Collaborating with other developers
  • Bitbucket Git account

MODULE 1: BIG DATA INTRODUCTION 

  • Big Data Overview
  • Five Vs of Big Data
  • What is Big Data and Hadoop
  • Introduction to Hadoop
  • Components of Hadoop Ecosystem
  • Big Data Analytics Introduction

MODULE 2: HDFS AND MAP REDUCE 

  • HDFS – Big Data Storage
  • Distributed Processing with Map Reduce
  • Mapping and reducing  stages concepts
  • Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort
  • Hands-on Map Reduce task

MODULE 3: PYSPARK FOUNDATION 

  • PySpark Introduction
  • Spark Configuration
  • Resilient distributed datasets (RDD)
  • Working with RDDs in PySpark
  • Aggregating Data with Pair RDDs

MODULE 4: SPARK SQL and HADOOP HIVE 

  • Introducing Spark SQL
  • Spark SQL vs Hadoop Hive
  • Working with Spark SQL Query Language

MODULE 5: MACHINE LEARNING WITH SPARK ML 

  • Introduction to MLlib Various ML algorithms supported by MLib
  • ML model with Spark ML
  • Linear regression
  • logistic regression
  • Random forest

MODULE 6: KAFKA and Spark 

  • Kafka architecture
  • Kafka workflow
  • Configuring Kafka cluster
  • Operations

MODULE 1: BUSINESS INTELLIGENCE INTRODUCTION 

  • What Is Business Intelligence (BI)?
  • What Bi Is The Core Of Business Decisions?
  • BI Evolution
  • Business Intelligence Vs Business Analytics
  • Data Driven Decisions With Bi Tools
  • The Crisp-Dm Methodology

MODULE 2: BI WITH TABLEAU: INTRODUCTION 

  • The Tableau Interface
  • Tableau Workbook, Sheets And Dashboards
  • Filter Shelf, Rows And Columns
  • Dimensions And Measures
  • Distributing And Publishing

MODULE 3 : TABLEAU: CONNECTING TO DATA SOURCE 

  • Connecting To Data File , Database Servers
  • Managing Fields
  • Managing Extracts
  • Saving And Publishing Data Sources
  • Data Prep With Text And Excel Files
  • Join Types With Union
  • Cross-Database Joins
  • Data Blending
  • Connecting To Pdfs

MODULE 4 : TABLEAU : BUSINESS INSIGHTS 

  • Getting Started With Visual Analytics
  • Drill Down And Hierarchies
  • Sorting & Grouping
  • Creating And Working Sets
  • Using The Filter Shelf
  • Interactive Filters
  • Parameters
  • The Formatting Pane
  • Trend Lines & Reference Lines
  • Forecasting
  • Clustering

MODULE 5 : DASHBOARDS, STORIES AND PAGES 

  • Dashboards And Stories Introduction
  • Building A Dashboard
  • Dashboard Objects
  • Dashboard Formatting
  • Dashboard Interactivity Using Actions
  • Story Points
  • Animation With Pages

MODULE 6 : BI WITH POWER-BI 

  • Power BI basics
  • Basics Visualizations
  • Business Insights with Power BI

MODULE 1: ARTIFICIAL INTELLIGENCE OVERVIEW 

  • Evolution Of Human Intelligence
  • What Is Artificial Intelligence?
  • History Of Artificial Intelligence
  • Why Artificial Intelligence Now?
  • Ai Terminologies
  • Areas Of Artificial Intelligence
  • Ai Vs Data Science Vs Machine Learning

MODULE 2: DEEP LEARNING INTRODUCTION 

  • Deep Neural Network
  • Machine Learning vs Deep Learning
  • Feature Learning in Deep Networks
  • Applications of Deep Learning Networks

MODULE 3: TENSORFLOW FOUNDATION 

  • TensorFlow Installation and setup
  • TensorFlow Structure and  Modules
  • Hands-On: ML modeling with TensorFlow

MODULE 4: COMPUTER VISION INTRODUCTION 

  • Image Basics
  • Convolution Neural Network (CNN)
  • Image Classification with CNN
  • Hands-On: Cat vs Dogs Classification with CNN Network

MODULE 5: NATURAL LANGUAGE PROCESSING (NLP) 

  • NLP Introduction
  • Bag of Words Models
  • Word Embedding
  • Language Modeling
  • Hands-On: BERT  Algorithm

MODULE 6: AI ETHICAL ISSUES AND CONCERNS 

  • Issues And Concerns Around Ai
  • Ai And Ethical Concerns
  • Ai And Bias
  • Ai: Ethics, Bias, And Trust

MODULE 1: NEURAL NETWORKS 

  • Structure of neural networks
  • Neural network - core concepts
  • Feed forward algorithm
  • Backpropagation
  • Building neural network from scratch using Numpy

MODULE 2: IMPLEMENTING DEEP NEURAL NETWORKS 

  • Introduction to neural networks with tf2.X
  • Simple deep learning model in Keras (tf2.X)
  • Building neural network model in TF2.0 for MNIST dataset

MODULE 3: DEEP COMPUTER VISION - CNN 

  • Convolutional neural networks (CNNs)
  • Introduction
  • CNNs with Keras
  • Transfer learning in CNN
  • Style transfer
  • Flowers dataset with tf2.X
  • Examining x-ray with CNN model

MODULE 4 : RECURRENT NEURAL NETWORK 

  • RNN introduction
  • Sequences with RNNs
  • Long short-term memory networks
  • LSTM RNNs and GRU
  • Examples of RNN applications

MODULE 5: NATURAL LANGUAGE PROCESSING (NLP) 

  • Natural language processing
  • Introduction
  • NLP with RNNs
  • Creating model
  • Transformers and BERT
  • State of art NLP and projects

MODULE 6: REINFORCEMENT LEARNING 

  • Markov decision process
  • Fundamental equations in RL
  • Model-based method
  • Dynamic programming model free methods

MODULE 7: DEEP REINFORCEMENT LEARNING 

  • Architectures of deep Q learning
  • Deep Q learning
  • Policy gradient methods

MODULE 8: GENERATIVE ADVERSARIAL NETWORK (GAN) 

  • Gan introduction
  • Core concepts of GAN
  • Building GAN model with TensorFlow 2.X
  • GAN applications

MODULE 9: DEPLOYING DL MODELS IN THE CLOUD (AWS) 

  • Amazon web services (AWS)
  • AWS SageMaker Overview
  • Sage Makers from Data pipeline to deployments
  • Deploying deep learning models WS Sage maker

OFFERED ARTIFICIAL INTELLIGENCE COURSES IN BANGALORE

ARTIFICIAL INTELLIGENCE TRAINING REVIEWS

ABOUT ARTIFICIAL INTELLIGENCE TRAINING IN BANGALORE

Bangalore, often referred to as India's Silicon Valley, is taking center stage in the global Artificial Intelligence (AI) revolution. According to Allied Market Research, the AI market is poised for remarkable growth, expected to soar from $153.6 billion in 2023 to an estimated $3,636 billion by 2033, boasting a striking 37.3% CAGR. In response to this demand, DataMites offers practical, offline artificial intelligence courses in Bangalore, complete with internship opportunities and job placement support, preparing a new generation of skilled data science professionals for the evolving landscape.

At the heart of Bangalore's tech revolution, DataMites stands as a leader in artificial intelligence courses in Bangalore, offering unmatched Artificial Intelligence training programs. The Artificial Intelligence Engineer Course caters to both novice and intermediate data science enthusiasts. It fuses key components from ArtificiaI Intelligence Expert and Certified Data Scientist, offering a career-oriented base with topics like statistics, mathematics, Python, and extensive machine learning.

DataMites Innovative 3 Phase Artificial Intelligence Courses in Bangalore

Phase 1 - Foundation in Self-Study: Our approach begins with self-study through comprehensive video materials, setting a strong foundation in AI basics.

Phase 2 - Dynamic and Detailed Training: We provide a choice of online artificial intelligence courses in Bangalore or in-person artificial intelligence classroom training in Bangalore, encompassing a 300-hour deep dive over three months. This phase includes an extensive syllabus, project-based learning, and expert mentorship.

Phase 3 - Phase 3: Internship + Placement Support: Gain practical experience through 10 Capstone Projects, a client project, and earn a valuable artificial intelligence internship certification in Bangalore

Our dedicated Placement Assistance Team (PAT) in the artificial intelligence training program in Bangalore offers comprehensive career guidance and assistance, ensuring a seamless transition into AI careers. Our artificial intelligence training with placement emphasizes practical proficiency, preparing you effectively for your artificial intelligence career.

Other Artificial Intelligence Certifications in Bangalore at DataMites

DataMites proudly offers a variety of specialized artificial intelligence certifications in Bangalore tailored to different career objectives:

Artificial Intelligence Foundation: A beginner-level course offering a comprehensive introduction to AI principles and theories.

Artificial Intelligence for Managers: Designed for business leaders, this course focuses on the strategic integration of AI in corporate strategies.

Artificial Intelligence Expert: The Artificial Intelligence Expert Course is expertly designed for individuals ranging from beginners to intermediate learners in the data science domain.

Certified NLP Expert: Concentrating on Natural Language Processing, ideal for those intrigued by AI's potential in language understanding.

DataMites Comprehensive Artificial Intelligence Course Structure in Bangalore

DataMites offers two flagship Artificial Intelligence Courses - AI Expert and AI Engineer.

When it comes to artificial intelligence education, our Artificial Intelligence Expert Training in Bangalore is second to none in the industry. We consistently update the course to meet industry standards, providing a well-structured learning process that facilitates lean and effective learning.

 

MODULE 1: NEURAL NETWORKS

- Exploring neural network structures

- Understanding core neural network concepts

- Implementing the feedforward algorithm

- Applying backpropagation for learning

- Building neural networks from scratch using Numpy.

 

MODULE 2: IMPLEMENTING DEEP NEURAL NETWORKS

- Introduction to neural networks with tf2.X

- Creating a basic deep learning model in Keras (tf2.X)

- Building a neural network model in TF2.0 for the MNIST dataset

 

MODULE 3: DEEP COMPUTER VISION - CNN

- Introduction to Convolutional Neural Networks (CNNs)

- Building CNNs with Keras

- Leveraging transfer learning in CNN

- Exploring style transfer techniques

- Working with the Flowers dataset using tf2.X

- Analyzing X-ray images with a CNN model

 

MODULE 4: NATURAL LANGUAGE PROCESSING (NLP)

- Introduction to Natural Language Processing (NLP)

- Implementing NLP with Recurrent Neural Networks (RNNs)

- Creating NLP models for text analysis

- Introduction to Transformers and BERT for NLP

- Real-world NLP project examples

 

MODULE 5: RECURRENT NEURAL NETWORK

- Introduction to Recurrent Neural Networks (RNNs)

- Working with sequential data using RNNs

- Utilizing Long Short-Term Memory Networks (LSTM) and GRU

- Exploring real-world applications of RNNs

 

MODULE 6: DEEP REINFORCEMENT LEARNING

- Understanding the architectures of Deep Q Learning

- Implementing Deep Q Learning algorithms

- Exploring policy gradient methods

 

MODULE 7: GENERATIVE ADVERSARIAL NETWORK (GAN)

- Introduction to Generative Adversarial Networks (GANs)

- Grasping core concepts of GANs

- Building GAN models using TensorFlow 2.X

- Applying GANs to real-world scenarios.

 

MODULE 8: DEPLOYING DL MODELS IN THE CLOUD (AWS)

- Introduction to Amazon Web Services (AWS)

- Overview of AWS SageMaker

- Managing data pipelines and model deployments with SageMaker

- Deploying deep learning models efficiently on AWS SageMaker

Our Artificial Intelligence Engineer Training is widely regarded as the industry's premier choice for AI education. We continually update the curriculum to stay current with evolving industry demands, ensuring that our students receive the latest knowledge and skills. 

In the AI Engineer Course, we offer a comprehensive blend of the AI Expert and Certified Data Scientist (CDS) programs. This integration provides a well-rounded education in artificial intelligence and data science. The course covers various topics from the CDS curriculum, including:

  1. Python Foundation

  2. Data Science Foundations

  3. Machine Learning Expert

  4. Advanced Data Science

  5. Version Control with Git

  6. Big Data Foundation

  7. Certified BI Analyst

  8. Database: SQL and MongoDB

  9. Artificial Intelligence Foundation

These subjects from the CDS course form a strong foundation and expertise in data science, seamlessly incorporated into the AI Engineer Course. This holistic approach equips our students with the knowledge and skills required to excel in the ever-evolving field of artificial intelligence.

DataMites Artificial Intelligence Course Tools in Bangalore

At DataMites, our Artificial Intelligence Courses in Bangalore span a wide spectrum of AI tools, ensuring you develop the crucial skills and expertise required. These tools encompass:

  1. Anaconda

  2. Numpy

  3. Python

  4. Apache Pyspark

  5. Git

  6. Hadoop

  7. MongoDB

  8. Amazon SageMaker

  9. Google Bert

  10. Google Colab

  11. Advanced Excel

  12. MySQL

  13. Scikit Learn

  14. Azure Machine Learning

  15. Flask

  16. Apache Kafka

  17. Power BI

  18. GitHub

  19. TensorFlow

  20. Pandas

  21. Tableau

  22. Atlassian BitBucket

  23. Natural Language Toolkit

  24. PyCharm

Reasons to Choose DataMites for Artificial Intelligence Training in Bangalore:

Expert Guidance: Led by the globally recognized AI expert, Ashok Veda.

Internationally Valued Certifications: Our certifications are accredited by prestigious organizations like IABAC and NASSCOM FutureSkills.

Advanced Educational Resources: We provide cutting-edge learning materials and methodologies.

Project-Based Learning: Emphasizing practical experience through varied project work.

Flexible Learning Modes: Available both artificial intelligence training online in Bangalore and artificial intelligence training offline in Bangalore at prime Bangalore locations like BTM, Marathahalli, and Kudlu Gate.

Artificial Intelligence Internships in Bangalore

In Bangalore, Artificial Intelligence Internships are essential for converting theoretical AI knowledge into practical expertise. They offer students the opportunity to apply academic concepts in real-world scenarios, enhancing their skills and understanding. These internships are invaluable in preparing students for the complexities and challenges of the fast-evolving AI industry.

DataMites provides Artificial Intelligence Courses with Internship in Bangalore, offering a holistic learning experience. This combination of classroom knowledge and practical application equips students with the tools needed to excel in the AI field. Our internships are designed to develop industry-ready AI professionals, setting the foundation for successful and innovative careers in Artificial Intelligence.

DataMites Artificial Intelligence Placement Programs in Bangalore

In Bangalore's vibrant tech sector, effective artificial intelligence placement programs are crucial for transitioning from academic learning to professional AI roles. These programs effectively bridge the gap between education and industry needs, opening doors to rewarding AI career opportunities. 

DataMites provides artificial intelligence courses with placement in Bangalore, preparing students academically and professionally for the AI job market. Our initiatives connect students with top tech firms, facilitating their successful integration into the AI industry and fostering thriving careers in Artificial Intelligence.

Home to some of the best technical institutes in India, Bangalore  churns out a large number of engineers and data scientists annually, many of whom gravitate towards AI and machine learning. The Artificial Intelligence (AI) industry in Bangalore is thriving, offering a range of artificial intelligence job roles in Bangalore including AI engineers, machine learning specialists, data analysts, and AI project managers. These positions are pivotal in driving the city's AI innovation and development.

In terms of compensation, AI engineers in Bangalore enjoy lucrative salaries, ranging from INR 3.3 lakhs to INR 22 lakhs per year, with an average AI engineers salary in Bangalore of around INR 8.6 lakhs, as reported by AmbitionBox. This reflects the high potential of the AI sector in Bangalore. Comparatively, the average salary for an AI Engineer in India stands at INR 11.58 lakhs per year, as per Glassdoor. This lucrative salary range, coupled with Bangalore's dynamic technology environment, makes it an ideal place for AI professionals to flourish.

With AI becoming increasingly integral across various industries, the demand for skilled AI professionals is on the rise. Recognized internationally, our institute offers an extensive range of courses, extending beyond AI to embrace areas like data science, machine learning, data analytics, and data engineer. Our mission is to prepare individuals for a future shaped by AI, with a curriculum that spans the full spectrum of next-generation technologies. 

DESCRIPTION OF ARTIFICIAL INTELLIGENCE COURSE IN BANGALORE

Artificial Intelligence is a branch of Computer Science which talks about incorporating the reasoning and decision making capabilities demonstrated by humans, into a machine, which makes it possible for the machine to exercise the critical tasks which require human intervention.

The Artificial Intelligence Engineer course offered by DataMites consists of a bundle of different courses- Artificial Intelligence Foundation, Machine Learning, Tensorflow 2.X Platform, Core Learning Algorithms, Neural Networks, Implementing Deep Neural Networks, Reinforcement Learning, Natural Language Processing, etc. 

The Artificial Intelligence Engineer is the most comprehensive course with the following features:- 

  • Globally Recognised Certification- IABAC 

  • 6 months of live online training.

  • Training by industry experts.

  • Internship Opportunities(10 Capstone Projects and 1 Client Project)

Machine Learning is a branch of Artificial Intelligence, which concerns the ability of machines to learn from experience and subsequently improve themselves, without being influenced by another person.

Deep Learning is a part of Artificial Intelligence and Machine Learning. To be precise, when the data is huge in numbers, Machine Learning doesn’t hold good, as they are incapable of going deep into the data sets. Deep Learning helps to address this problem.  The structure of Deep Learning comprises Artificial Neural Networks which resemble the neuron structure in the human brain. These networks have different layers and are capable enough to pierce inside the large data set to retrieve the relevant information.

The prerequisites to pursue an  AI Engineer course are:

Educational Qualifications

  •  Graduation/PG in Computer Science, IT, Statistics

  •  Certification in Data Science, Machine Learning, Deep Learning, etc.

Some of the technical skills that would prove advantageous in learning an Artificial Intelligence course are:-

  • Knowledge of Mathematics and Statistics.

  • Knowledge of Algorithms.

  • Knowledge of programming languages- C, C++, Java

  • Knowledge of Neural Networks

  • Knowledge of Natural Language Processing- NLP Libraries

Some of the business skills that would prove advantageous in learning an Artificial Intelligence course are:-

  • Analytical Skills

  • Problem Solving 

  • Communication Skills

  • Business Acumen

Python is the most preferred among programming languages in the field of Data Science and Artificial Intelligence. As far as Data Scientist is concerned Python is the most effective programming language, with a lot of libraries available. Python can be deployed at every phase of data science functions. It is beneficial in capturing data and importing it into SQL. Python can also be used to create data sets. 

The Artificial Intelligence course offered by DataMites comprises a topic on Python Programming language. Having a basic understanding of Python is an added advantage for the Artificial Intelligence course.

Machine Learning and Artificial Intelligence are two inter-related topics. The Artificial intelligence course provided by DataMites comprises Machine Learning as a part of its syllabus. However, a basic knowledge of Machine Learning would be an advantage while joining the course.

Yes. The Artificial Intelligence course provided by DataMites covers a topic on Python. It includes concepts such as Building ML Classification Models with Python, Building ML Regression Models with Python, CIFAR-10 classification with Python, Transfer Learning In Python, RNNS In Python

DataMites offers an Artificial Intelligence course in three different modes. The Live Virtual/Online and Classroom training is offered at a fee/cost of Rs 99000/-, and the Self Learning mode is offered at Rs 69000/-.

P.G degree is not a mandatory requirement to pursue an Artificial Intelligence certification. However, a sound knowledge of Technology, Engineering, and Management domains will be an added advantage.

Artificial Intelligence is present everywhere nowadays and is used across functions like Finance, Healthcare, Education, Manufacturing, Retail, Customer Service, etc. Therefore learning Artificial Intelligence will help to increase the chances of your employability in various sectors. AI is also an indispensable factor, for the reason that most of the data today are stored digitally. The potential of AI to be incorporated into data helps in making the right decisions.

The Artificial Intelligence course in Bangalore offered by DataMites helps to give you a clear picture of the role of AI in the decision-making and problem-solving process.

This Artificial Intelligence course enables you to:-

  • Understand AI and its relevance in bringing in change in the current industrial scenario.

  • Learn the terminologies that are used in the AI domain.

  • Gain practical knowledge of employing AI and related disciplines in solving complex real-world problems.

  • Make decision making easy.

Bangalore is known for lots of business opportunities and large corporate houses adorning the city. This, in turn, contributes to new employment opportunities being created. 

Learning the Artificial Intelligence course in Bangalore helps you to leverage the available opportunities and also prepares you for the challenges. Artificial Intelligence is a discipline that is influencing the present in a big way and is expected to grow in the future. Therefore by learning AI you are at the advantage of remaining well equipped in advance to cope with the changing times.

DataMites in Bangalore offers the most comprehensive Artificial Intelligence course that is aligned with the state of art industry best practices in the Artificial Intelligence domain.

Bangalore has a lot of business opportunities with large corporates gracing the city. The career opportunities in Artificial Intelligence are booming and Bangalore is no exception.

DataMites in Bangalore provides the most comprehensive Artificial Intelligence Engineer course with the following features.

  • Globally Recognised Certification- IABAC 

  • Experienced Trainers

  • Industry aligned courses

  • Internship Opportunities

  • Job assistance

DataMites caters to graduates and professionals equally. Therefore, DataMites is the best choice for anyone who wishes to become an Artificial Intelligence Engineer in Bangalore.

Bangalore, in India, is known for lots of business opportunities. It consists of many large companies, business houses, with large amounts of transactions happening every day, as a result of which there is an equally large amount of data generated daily. Also, India. is known for many recognised universities. Learning Artificial Intelligence in India will be a great opportunity for students as well as professionals.

DataMites in Bangalore provides the most comprehensive Artificial Intelligence course that is designed as per the current industry requirements. Also, the Artificial Intelligence course provided by DataMites in Bangalore is certified in collaboration with IABAC.

On completing the Artificial Intelligence course DataMites in Bangalore you will be eligible for the following job roles:-

  • Artificial Intelligence Engineer

  • Data Scientist

  • Machine Learning Expert

  • Analytics Manager

The market for Artificial Intelligence in Bangalore is booming and is expected to grow in the future. As AI requires the mastering of various disciplines and there are only a few who are good at all of them, the one who can master all the disciplines is at a greater advantage. Career Opportunities in AI are plenty but there is a shortage of skilled AI professionals, therefore there is also a rising demand for the same. Some of the top industries in Bangalore for AI are- Banking and Finance,  Information and Communication, Administration, and Support Services.

According to payscale.com the average salary of an Artificial Intelligence Engineer in Bangalore is Rs 7,30,000 per year.

India has a good number of small, medium, and large corporations. The opportunity in Artificial Intelligence in India is also plenty. As AI has shown us a way to tackle real-world complexities, the need to incorporate AI into various functions is equally important. All the present-day organisations are well aware of this and have acknowledged this to a great extent.  In simple words, most companies nowadays have found a better way of tackling their day- to day problems with the help of AI. 

Every company in India(Be it Small, Medium, and Large enterprises) requires AI professionals as all of them work on their data and requires some or the other AI expertise to be deployed into the tasks.

Artificial Intelligence, Machine, and Data Science contribute to one another in one or the other way.  Python and R are the two programming languages that are used in the data science process. Some of the reasons, for python being the most preferred programming language in comparison to R:-

  • Easy to learn: Python is easier to understand and master, in comparison to R 

  • Flexible: The flexibility offered by Python offers is better when compared to the R programming language.

  • Availability of libraries: Python has a wide range of libraries available, such as pandas, scikit-learn, etc. This makes it easier in handling machine learning projects.

  • Data visualization: By using matplotlib in Python, you can do the plotting of complex data representations into 2D plots. Data visualization is a significant process in the job of a data scientist. Python can be used for Data Visualisation. 

However as far as Artificial Intelligence is concerned, learning both Python and R will be advantageous.

The instructors at DataMites institute are industry experts who have a good number of years of experience in the field of Artificial Intelligence.

Enrolling in online training online is very simple. The payment can be done using your debit/credit card that includes Visa Card, MasterCard; American Express, or PayPal. You will receive the receipt after the payment is successful. You can get in touch with our educational counsellor for more information.

DataMites conducts classes for Artificial Intelligence courses both during Weekdays and Weekends. You can opt between the two according to your convenience.

DataMites conducts both morning and evening classes for Artificial Intelligence courses in Bangalore. You can opt between the two as per your convenience.

Yes. DataMites provides an online lab facility called Pro Lab. You can log in with a username to use this facility.

Yes, DataMites has partnered with many AI companies and provides live Artificial Intelligence projects to work on which helps the candidate to get exposure to the real-world working environment. DataMites provides 10 Capstone projects and 1 client project as part of the Artificial Intelligence course.

The DataMites Placement Assistance Team(PAT)  helps the candidates to have an easy start in his/her career. The team offers services like Resume Building, Interview Preparation. The team will assist you in the following areas;-

Project Mentoring- 100 hrs Live mentoring in industry projects.

Interview Preparations- Mock Interview sessions.

Resume Support- Personal guidance in resume creation by professionals.

Doubt clearing sessions- Live doubt clearing sessions on 

Job updates- Interview connects.

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FAQ’S OF ARTIFICIAL INTELLIGENCE TRAINING IN BANGALORE

The training provided by DataMites for Artificial Intelligence in Bangalore is primarily online. However, classroom training can be made available if there is adequate demand.

DataMites is a global institute that offers comprehensive courses in Artificial Intelligence. The syllabus is designed in tune with the current industry trends and helps to cater to the needs of fresh AI aspirants and experienced professionals. The Artificial Intelligence course offered by DataMites is unique in the following ways.

DataMites offers an Artificial Intelligence course in Bangalore in three different modes. The Live Virtual/Online and Classroom training is offered at a fee/cost of Rs 99000/-, and the Self Learning mode is offered at Rs 69000/-.

DataMites in Bangalore offers certifications in collaboration with IABAC. IABAC is a global body, which offers certifications in Business Analytics and Data Science. IABAC is founded on the principles of the EDISON Data Science Framework (EDSF). DataMites provides a range of certifications in Data Science, Machine Learning, Artificial Intelligence. All the data science certifications offered by DataMites are structured based on the industry trends.

DataMites provides online training sessions for the Artificial Intelligence course in Bangalore. However, classroom mode of training can be made available if there is adequate demand for the same.

Yes. DataMites offers internship opportunities for the Artificial Intelligence course which helps you to get exposure,  understand and implement the concepts learned in the course to build AI models for solving real-world problems. DataMites provides 10 Capstone projects and 1 client project for the Artificial Intelligence course.

Yes. You will learn Deep Learning as a part of the AI Engineer course. It includes - Layers, Loss Function, Optimization, Model Training, and Evaluation, etc.

Yes. You will learn Computer Vision as a part of the Artificial Intelligence course. It includes - Convolutional Neural Networks, CNN with KERAS, Transfer Learning, etc.

Yes. You will learn Neural Networks as a part of the Artificial Intelligence course. It includes - Core Concepts of Neural Networks, Structure of Neural Networks, Back Propagation, etc.

The Artificial Intelligence course offered by DataMites in Bangalore covers the following topics:-

  • Artificial Intelligence Foundation.

  • Machine Learning 

  • Tensorflow

  • Core Learning Algorithms 

  • Neural Networks

  • Natural Language Processing(NLP)

  • Deep Computer Vision- Convolutional Neural Networks

  • Reinforcement Learning.

The duration of the Artificial Intelligence course provided by DataMites in Bangalore is 6 months with 120 hrs of live online training conducted by industry experts.

Artificial Intelligence is a vast subject for study, it is a mix of Statistics and Computer Science. DataMites in Bangalore offers quality training sessions in Artificial Intelligence, Machine Learning, etc. The Artificial Intelligence courses provided by DataMites in Bangalore are exclusively designed in tune with the current industry requirements. Also with many projects to work on, under the mentoring of industry experts.

DataMites offers an Artificial Intelligence course in Bangalore in three different modes. The Live Virtual/Online and Classroom training is offered at a fee/cost of Rs 99000/-, and the Self Learning mode is offered at Rs 69000/-.

The registrations cancelled within 48 hrs of enrollment will be refunded in full. The processing time of the refund is within 30 days, from the date of the receipt of the cancellation request.

You have access to the online study materials from 6 months up to 1 year.

DataMites accepts all the online payments(Debit/Credit)for the AI course in Bangalore through Razor pay. If you opt to pay through your credit card there will be an EMI option. DataMites collect token advance during the time of registration and the remaining payment should be settled in full before the completion of the course.

All the online sessions are recorded. If you happen to miss a session you can access the online recording.

Yes. The Artificial Intelligence certification exam fee is included in the total course fee. Therefore once you are registered for a course, you are also eligible to attend the exam.

Yes. You will learn Natural Language Processing(NLP) as a part of the Artificial Intelligence course. It includes - The Basics of Natural Language Processing, Integer Coding, Word Embedding, and Bag Of Words.

Yes. One of the courses out of the bundle of AI course talks about Reinforcement Learning. It includes- Markov Decision Process, Fundamental Equations in Reinforcement Learning.

Yes. One of the courses out of the bundle of AI course talks about Tensorflow. It includes-Basics of Tensorflow, Installation and Basic Operation in Tensorflow, Tensorflow 2.0 Eager Mode.

Yes. One of the courses out of the bundle of AI course talks about Machine Learning. It includes-Basics of Machine Learning, Mathematics for Machine Learning.

Yes. One of the courses out of the bundle of AI course talks about Python. It includes-

Yes, the  Artificial Intelligence Engineer course provided by DataMites comprises a topic on Machine Learning in the syllabus. Therefore when you learn the AI course, you also get an opportunity to learn Machine Learning. The Machine Learning topics covered are:-

Machine Learning Overview, Mathematics for Machine Learning, Advanced Machine Learning Concepts, etc.

Yes. DataMites will provide you with a course completion certificate after you clear the AI certification examination.

The AI course offered by DataMites in Bangalore includes 10 capstone projects and 1 client project.

The mode of training offered by DataMites in Bangalore is primarily online. However, classroom training can be made available in Bangalore,  if there is adequate demand for the same.

DataMites is a global institute for Artificial Intelligence education. It has a history of training for more than 15000 candidates. The syllabus provided by DataMites in Bangalore is exclusively designed in tune with the current industry trends. The following makes DataMites unique from others:-

  • Globally Recognised Certification- IABAC 

  • Experienced Trainers

  • Industry aligned courses

  • Internship Opportunities

  • Career Guidance

  • More than 15000 certified learners

DataMites provides Flexi Pass, which gives you the privilege to attend unlimited batches in a year. The Flexi Pass is specific to one particular course. Therefore if you have a Flexi pass for a particular course of your choice, you will be able to attend any number of sessions of that course. It is to be noted that a Flexi pass is valid for a particular period.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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