ARTIFICIAL INTELLIGENCE CERTIFICATION AUTHORITIES

Artificial Intelligence Course Features

ARTIFICIAL INTELLIGENCE LEAD MENTORS

ARTIFICIAL INTELLIGENCE COURSE FEE IN FARIDABAD

Live Virtual

Instructor Led Live Online

154,000
81,900

  • 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
57,900

  • 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
86,900

  • 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 FARIDABAD

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 COURSE

Why DataMites Infographic

SYLLABUS OF AI COURSE IN FARIDABAD

MODULE 1 : ARTIFICIAL INTELLIGENCE OVERVIEW 

• Evolution Of Human Intelligence
• What Is Artificial Intelligence?
• History Of Artificial Intelligence
• Why Artificial Intelligence Now?
• 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

MODULE3 : TENSORFLOW FOUNDATION

• 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
• 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 : PYTHON BASICS 

 • Introduction of python
 • Installation of Python and IDE
 • Python Variables
 • Python basic data types
 • Number & Booleans, strings
 • Arithmetic Operators
 • Comparison Operators
 • Assignment Operators

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
 • Basics of List
 • List: Object, methods
 • Tuple: Object, methods
 • Sets: Object, methods
 • Dictionary: Object, methods

MODULE 4 : PYTHON FUNCTIONS 

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

MODULE 1 : OVERVIEW OF STATISTICS 

 • Introduction to 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
 • Types of Sampling
 • Simple Random Sampling
 • Stratified Random Sampling
 • Cluster Random Sampling
 • Systematic Random Sampling
 • Multi stage Sampling
 • 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 & Properties
 • Z Value / Standard Value
 • Empherical Rule and Outliers
 • Central Limit Theorem
 • Normality Testing
 • Skewness & Kurtosis
 • Measures Of Distance: Euclidean, Manhattan And Minkowski Distance
 • Covariance & Correlation

MODULE 4 : HYPOTHESIS TESTING 

 • Hypothesis Testing Introduction
 • P- Value, Critical Region
 • Types of Hypothesis Testing
 • Hypothesis Testing Errors : Type I And Type II
 • Two Sample Independent T-test
 • Two Sample Relation T-test
 • One Way Anova Test
 • Application of Hypothesis testing

MODULE 1: MACHINE LEARNING INTRODUCTION 

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

MODULE 2: PYTHON NUMPY  PACKAGE 

• Introduction to Numpy Package
 • Array as Data Structure
 • Core Numpy functions
 • Matrix Operations, Broadcasting in Arrays

MODULE 3: PYTHON PANDAS PACKAGE

 • Introduction to Pandas package
 • Series in Pandas
 • Data Frame in Pandas
 • File Reading in Pandas
 • Data munging with Pandas

MODULE 4:  VISUALIZATION WITH PYTHON - Matplotlib 

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

MODULE 5: PYTHON VISUALIZATION PACKAGE - SEABORN

 • Seaborn: Basic Plot
 • Advanced Python Data Visualizations

MODULE 6: ML ALGO: LINEAR REGRESSION

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

MODULE 7: ML ALGO: LOGISTIC REGRESSION 

 • Introduction to Logistic Regression
 • How it works: Classification & Sigmoid Curve
 • Modeling and Evaluation 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 9: ML ALGO: KNN

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

MODULE 1:  FEATURE ENGINEERING 

 • Introduction to Feature Engineering
 • Feature Engineering Techniques: Encoding, Scaling, Data Transformation
 • Handling Missing values, handling outliers
 • Creation of Pipeline
 • Use case for feature engineering

MODULE 2: ML ALGO: SUPPORT VECTOR MACHINE (SVM)

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

MODULE 3: PRINCIPAL COMPONENT ANALYSIS (PCA)

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

MODULE 4: ML ALGO: DECISION TREE 

 • Introduction to Decision Tree & Random Forest
 • How it works
 • Modeling and Evaluation in Python

MODULE 5: ENSEMBLE TECHNIQUES - BAGGING

 • Introduction to Ensemble technique 
 • Bagging and How it works
 • Modeling and Evaluation in Python

MODULE 6: ML ALGO: NAÏVE BAYES

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

MODULE 7:  GRADIENT BOOSTING, XGBOOST 

 • Introduction to Boosting and XGBoost
 • How it works?
 • Modeling and Evaluation of in Python

MODULE 1: TIME SERIES FORECASTING - ARIMA 

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

MODULE 2:  SENTIMENT ANALYSIS

 • Introduction to Sentiment Analysis
 • NLTK Package
 • Case study: Sentiment Analysis on Movie Reviews

MODULE 3:  REGULAR EXPRESSIONS WITH PYTHON 

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

MODULE 4: ML MODEL DEPLOYMENT WITH FLASK 

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

MODULE 5: ADVANCED DATA ANALYSIS WITH MS EXCEL 

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

MODULE 6:  AWS CLOUD FOR DATA SCIENCE

 • Introduction of cloud
 • Difference between GCC, Azure,AWS
 • AWS Service ( EC2 instance)

MODULE 7: AZURE FOR DATA SCIENCE

 • Introduction to AZURE ML studio
 • Data Pipeline
 • ML modeling with Azure

MODULE 8: INTRODUCTION TO DEEP LEARNING

 • Introduction to Artificial Neural Network, Architecture
 • Artificial Neural Network in Python
 • Introduction to Convolutional Neural Network, Architecture
 • Convolutional Neural Network in Python

MODULE 1: DATABASE INTRODUCTION

 • DATABASE Overview
 • Key concepts of database management
 • Relational Database Management System
 • CRUD operations

 MODULE 2: SQL BASICS

 • Introduction to Databases
 • Introduction to SQL
 • SQL Commands
 • MY SQL workbench installation

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
• Windows functions: Over, Partition , Rank 

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

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
 • Git Essentials: Copy & User Setup
 • Mastering Git and GitHub

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

MODULE 5: GIT WITH GITHUB AND BITBUCKET 

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

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

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

MODULE 1: TABLEAU FUNDAMENTALS 

 • Introduction to Business Intelligence & Introduction to Tableau
 • Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
 • Bar chart, Tree Map, Line Chart
 • Area chart, Combination Charts, Map
 • Dashboards creation, Quick Filters
 • Create Table Calculations
 • Create Calculated Fields
 • Create Custom Hierarchies

MODULE 2: POWER-BI BASICS 

 • Power BI Introduction 
 • Basics Visualizations
 • Dashboard Creation
 • Basic Data Cleaning
 • Basic DAX FUNCTION

MODULE 3 : DATA TRANSFORMATION TECHNIQUES

 • Exploring Query Editor
 • Data Cleansing and Manipulation:
 • Creating Our Initial Project File
 • Connecting to Our Data Source
 • Editing Rows
 • Changing Data Types
 • Replacing Values

MODULE 4 :  CONNECTING TO VARIOUS DATA SOURCES 

 • Connecting to a CSV File
 • Connecting to a Webpage
 • Extracting Characters
 • Splitting and Merging Columns
 • Creating Conditional Columns
 • Creating Columns from Examples
 • Create Data Model

MODULE 1: NEURAL NETWORKS 

 • Structure of neural networks
 • Neural network - core concepts(Weight initialization)
 • Neural network - core concepts(Optimizer)
 • Neural network - core concepts(Need of activation)
 • Neural network - core concepts(MSE & RMSE)
 • Feed forward algorithm
 • Backpropagation

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 - IMAGE RECOGNITION

• Convolutional neural networks (CNNs)
• CNNs with Keras-part1
• CNNs with Keras-part2
• Transfer learning in CNN
• Flowers dataset with tf2.X(part-1)
• Flowers dataset with tf2.X(part-2)
• Examining x-ray with CNN model

MODULE 4 : DEEP COMPUTER VISION - OBJECT DETECTION

 • What is Object detection
 • Methods of Object Detections
 • Metrics of Object detection
 • Bounding Box regression
 • labelimg
 • RCNN
 • Fast RCNN
 • Faster RCNN
 • SSD
 • YOLO Implementation
 • Object detection using cv2

MODULE 5: RECURRENT NEURAL NETWORK 

• RNN introduction
• Sequences with RNNs
• Long short-term memory networks(part 1)
• Long short-term memory networks(part 2)
• Bi-directional RNN and LSTM
• Examples of RNN applications

MODULE 6: NATURAL LANGUAGE PROCESSING (NLP)

• Introduction to Natural language processing
• Working with Text file
• Working with pdf file
• Introduction to regex
• Regex part 1
• Regex part 2
• Word Embedding
• RNN model creation
• Transformers and BERT
• Introduction to GPT (Generative Pre-trained Transformer)
• State of art NLP and projects

MODULE 7: PROMPT ENGINEERING

• Introduction to Prompt Engineering
• Understanding the Role of Prompts in AI Systems
• Design Principles for Effective Prompts
• Techniques for Generating and Optimizing Prompts
• Applications of Prompt Engineering in Natural Language Processing

MODULE 8: REINFORCEMENT LEARNING

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

MODULE 9: DEEP REINFORCEMENT LEARNING

• Architectures of deep Q learning
• Deep Q learning
• Reinforcement Learning Projects with OpenAI Gym

MODULE 10: Gen AI

• Gan introduction, Core Concepts, and Applications
• Core concepts of GAN
• GAN applications
• Building GAN model with TensorFlow 2.X
• Introduction to GPT (Generative Pre-trained Transformer)
• Building a Question answer bot with the models on Hugging Face

MODULE 11: Gen AI

• Introduction to Autoencoder
• Basic Structure and Components of Autoencoders
• Types of Autoencoders: Vanilla, Denoising, Variational, Sparse, and Convolutional Autoencoders
• Training Autoencoders: Loss Functions, Optimization Techniques
• Applications of Autoencoders: Dimensionality Reduction, Anomaly Detection, Image

OFFERED ARTIFICIAL INTELLIGENCE COURSES IN FARIDABAD

ARTIFICIAL INTELLIGENCE TRAINING REVIEWS

ABOUT ARTIFICIAL INTELLIGENCE TRAINING IN FARIDABAD

DataMites has established itself as a leading institution for Artificial Intelligence education, empowering professionals and students with industry-relevant expertise. With a proven history of training over 100,000 learners, DataMites is synonymous with quality and innovation in AI and machine learning education. Its meticulously crafted curriculum caters to diverse learning needs, guiding students from foundational concepts to advanced applications.

DataMites Artificial Intelligence course in Faridabad curriculum covers everything from data manipulation and visualization to advanced machine learning techniques, providing a comprehensive learning experience. The institute’s expert instructors, with years of industry experience, guide learners through the complexities of the subject matter with ease.

The Artificial Intelligence Engineer Course offered by DataMites, accredited by IABAC and NASSCOM FutureSkills, aligns with global industry standards. This 9-month, immersive training program is offered at an offline center in Faridabad, blending in-person instruction with practical learning. The course offers live projects, internships, and training designed to cater to both professionals and students. With dedicated placement support, participants acquire the skills and confidence needed to thrive in AI-driven industries.

IT Industry in Faridabad: A Growing Hub of Opportunities

Faridabad, a key industrial city in Haryana, is witnessing a gradual transformation into a budding IT hub. Traditionally recognized for its manufacturing and engineering industries, the city is now embracing IT-enabled services, software development, and digital technologies. With initiatives such as Smart City projects and dedicated IT zones, Faridabad is attracting investments and fostering innovation in the tech sector. The city's proximity to Delhi NCR enhances its strategic importance, offering businesses access to a large talent pool and robust infrastructure.

Neighboring cities like Delhi and Noida serve as major IT powerhouses, driving technological advancements in North India. Delhi boasts prominent IT parks like Okhla Industrial Area and DLF Cyber City, housing leading multinational firms and startups. It specializes in software development, IT-enabled services, and e-commerce. Similarly, Noida is home to renowned IT companies such as HCL Technologies, Tech Mahindra, and TCS. With supportive government policies, Noida has positioned itself as a center for innovation in sectors like artificial intelligence, data analytics, and cloud computing. Faridabad benefits from its proximity to these IT giants, creating a synergistic environment for tech professionals and businesses.

Why Choose Faridabad for Artificial Intelligence Training?

Faridabad, a rapidly growing city in the National Capital Region (NCR), is emerging as a promising destination for Artificial Intelligence (AI) training. Its strategic location, expanding technological infrastructure, and accessibility to a wide range of resources make it an ideal place for learners and professionals looking to advance their AI skills. Here’s why Artificial Intelligence Course Faridabad is a good choice:

  1. Proximity to Delhi NCR: Faridabad’s close proximity to Delhi, Gurgaon, and Noida gives access to a massive tech ecosystem, including startups, multinational corporations, and research centers. This creates abundant opportunities for internships, networking, and employment.
  2. Emerging IT and Tech Hub: Faridabad is steadily transforming into an IT and tech hub, with many organizations adopting AI and related technologies. This trend increases the demand for skilled AI professionals and ensures relevant, market-aligned training programs.
  3. Opportunities for Practical Application: With industries such as manufacturing, healthcare, retail, and logistics thriving in Faridabad, AI training often includes practical applications tailored to these sectors. According to Ambitious Box, the average salary for an AI Engineer in Faridabad is 5 lakhs per year.

Career Prospects in Artificial Intelligence in Faridabad

Artificial Intelligence Training in Faridabad has emerged as one of the most transformative technologies of our time, with applications spanning industries such as healthcare, finance, automotive, education, and more. As AI adoption continues to grow, so do the career prospects for professionals skilled in AI and related fields. Below is an overview of the exciting career opportunities in AI:

  1. AI Engineers: Crafting algorithms and models for intelligent systems.
  2. Machine Learning Specialists: Developing advanced predictive and analytical tools.
  3. Data Scientists: Analyzing complex datasets to derive actionable insights.
  4. AI Consultants: Guiding businesses in leveraging AI for operational excellence.
  5. AI Researchers: Innovating new methodologies and technologies in artificial intelligence.

To succeed in these roles, professionals must develop key Artificial Intelligence skills, including proficiency in programming languages like Python or R, building machine learning models, working with neural networks, and utilizing tools such as TensorFlow and Keras. Expertise in big data frameworks like Hadoop and Spark, as well as experience with cloud platforms and AI ethics, can greatly enhance their competitive edge.

Moreover, strong soft skills, such as analytical thinking, problem-solving, and effective communication, are crucial for interpreting AI insights and presenting them clearly to stakeholders.

Why DataMites for Artificial Intelligence Training in Faridabad?

  1. Global Recognition: Our Artificial Intelligence courses in Faridabad are backed by credentials accredited by prestigious organizations like IABAC and NASSCOM FutureSkills.
  2. Expert Faculty: Gain insights from industry-leading professionals, including the distinguished AI specialist Ashok Veda, who bring practical expertise and real-world knowledge to the table.
  3. Flexible Learning Options: DataMites provides both online and on demand offline Artificial Intelligence courses in Faridabad, with a conveniently located offline center for easy accessibility.
  4. Practical Project and Internships: Our Artificial Intelligence Courses in Faridabad with internships, seamlessly combine academic learning with practical training.
  5. Placement Assistance: DataMites offers Artificial Intelligence courses in Faridabad with placement assistance, ensuring a seamless transition from education to employment.

Innovative 3-Phase Learning Methodology at DataMites

DataMites employs a structured 3-Phase Learning Methodology, designed to provide an engaging and practical educational experience.

Phase 1: Pre-Course Self-Study

Students begin their learning journey with premium video tutorials and in-depth study materials, building a solid foundation in artificial intelligence concepts.

Phase 2: Immersive Training

This phase consists of 20 hours of weekly training over a span of three months. Learners have the option to choose between live online sessions or offline artificial intelligence courses in Faridabad. The curriculum combines practical projects, expert guidance, and industry-focused content to deliver a comprehensive and enriching learning experience.

Phase 3: Internship & Placement Assistance

Students undertake 20 capstone projects and a client project, culminating in a distinguished internship certification. DataMites' Placement Assistance Team (PAT) provides personalized career support, helping students secure positions with top-tier companies.

Comprehensive Artificial Intelligence Curriculum

Our Artificial Intelligence Engineer Courses in Faridabad integrate the AI Expert and Certified Data Scientist (CDS) programs, offering a thorough and comprehensive education in artificial intelligence and data science. The Artificial Intelligence course curriculum covers a comprehensive range of topics, 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

This comprehensive approach ensures students gain the essential knowledge and skills needed to excel in the rapidly evolving field of artificial intelligence.

Additional AI Certifications from DataMites

  1. Artificial Intelligence for Managers: A specialized program designed for business leaders, focusing on integrating AI into strategic decision-making and optimizing business operations.
  2. Certified NLP Expert: A course dedicated to Natural Language Processing, perfect for individuals interested in exploring AI's capabilities in understanding and interpreting human language.
  3. Artificial Intelligence Expert: Tailored for beginners and intermediate data science professionals, this course provides a strong, career-focused foundation in AI.
  4. Artificial Intelligence Foundation: An introductory program offering a thorough understanding of AI's fundamental principles and core concepts.

DataMites Artificial Intelligence Course Tools in Faridabad

In our Artificial Intelligence Institute in Faridabad, we provide comprehensive coverage of a wide array of AI tools, ensuring you gain the essential skills and expertise. These tools encompass:

  1. Anaconda
  2. Python
  3. Apache Pyspark
  4. Git
  5. Hadoop
  6. MySQL
  7. MongoDB
  8. Amazon SageMaker
  9. Google Bert
  10. Google Colab
  11. Advanced Excel
  12. Scikit Learn
  13. Azure Machine Learning
  14. Flask
  15. Apache Kafka
  16. Power BI
  17. GitHub
  18. Numpy
  19. TensorFlow
  20. Pandas
  21. Tableau
  22. Atlassian BitBucket
  23. Natural Language Toolkit
  24. PyCharm

Elevate Your Artificial Intelligence Career in Faridabad

Artificial Intelligence (AI) is the driving force behind the digital revolution, paving the way for groundbreaking innovations. With the global AI market expected to reach a staggering $733.7 billion by 2027, industries across the world are embracing AI to enhance efficiency, improve decision-making, and unlock new possibilities. From self-driving cars and virtual assistants to healthcare diagnostics and personalized recommendations, AI is transforming the way we live, work, and interact with technology. The potential of Artificial Intelligence Certification in Faridabad is limitless, and the future holds exciting prospects for those who master this cutting-edge field.

Faridabad, located in the state of Haryana, is a growing city that forms part of the National Capital Region (NCR) in India. The city offers a favorable environment for AI professionals, with various opportunities in industries such as IT, manufacturing, healthcare, and finance. Faridabad's strategic location and well-connected infrastructure make it an ideal destination for individuals seeking quality AI education and career prospects. The city's dynamic business ecosystem and the presence of renowned companies provide a platform for AI enthusiasts to thrive and contribute to innovation and technological advancements.

Along with artificial intelligence courses, DataMites also provides data analytics, deep learning, python training, IoT, data engineer, mlops, tableau, data mining, python for data science, machine learning and data science courses.

ABOUT ARTIFICIAL INTELLIGENCE COURSE IN FARIDABAD

The term "Artificial Intelligence (AI)" refers to the development of intelligent machines capable of performing tasks that typically require human intelligence. This involves creating algorithms and systems that can learn, reason, perceive, and make decisions.

Steps to pursue a career as an AI engineer:

  • Develop a strong foundation in mathematics, computer science, and programming.
  • Acquire knowledge and understanding of AI concepts, algorithms, and technologies.
  • Learn programming languages commonly used in AI, such as Python or R.
  • Master machine learning and deep learning techniques.
  • Build a portfolio showcasing practical AI skills through projects.
  • Stay updated with the latest advancements and research in AI.

Several pioneers and contributors in the field of AI include Alan Turing, John McCarthy, Marvin Minsky, and Arthur Samuel. However, AI has evolved through the collective efforts of numerous researchers and scientists over time.

A career as an AI engineer is considered promising and rewarding. The demand for AI professionals is rapidly growing as organizations across industries adopt AI technologies. AI engineers have opportunities to work on cutting-edge projects, solve complex problems, and contribute to technological advancements. The field offers competitive salaries and continuous learning prospects.

Typically, a career in artificial intelligence requires:

  • A bachelor's or master's degree in computer science, AI, data science, or a related field.
  • Proficiency in programming languages like Python or Java.
  • Understanding of mathematics, including linear algebra, calculus, and statistics.
  • Familiarity with machine learning algorithms, neural networks, and deep learning frameworks.

The AI Engineer Course provides a comprehensive understanding of AI concepts, algorithms, and technologies. It covers topics such as machine learning, deep learning, natural language processing, computer vision, and AI deployment techniques. The curriculum includes hands-on projects and practical exercises to develop skills in building and deploying AI models.

To delve into Artificial Intelligence in Faridabad, it is helpful to have a basic understanding of programming concepts, familiarity with mathematics, and a curiosity to learn and explore AI technologies.

Transitioning into an artificial intelligence career from a different field can be achieved through several steps:

  • Gain foundational knowledge: Start by studying AI concepts, algorithms, and techniques through online courses, books, or tutorials.
  • Acquire programming skills: Learn programming languages commonly used in AI, such as Python or R, to implement AI models and algorithms.
  • Build a portfolio: Undertake AI projects and create a portfolio to demonstrate practical skills and showcase your abilities to potential employers.
  • Gain practical experience: Seek internships or freelance opportunities to gain hands-on experience and learn from industry professionals.
  • Network and join AI communities: Engage with AI professionals, attend conferences, and participate in AI-related events to expand your network and stay updated on industry trends.

Mastering Artificial Intelligence can be challenging due to the vastness and complexity of the field. It requires a solid foundation in mathematics, programming skills, and continuous learning to keep up with advancements. However, with dedication, practice, and ongoing learning, one can acquire proficiency in AI.

The AI For Managers Course covers topics such as AI basics, machine learning, deep learning, natural language processing, computer vision, AI implementation challenges, ethical considerations, and AI project management. It equips managers with the necessary knowledge to make informed decisions regarding AI adoption, implementation, and leveraging AI technologies for business growth.

Python is widely considered the best language for AI due to its simplicity, extensive libraries, and active community support. Python offers powerful libraries like TensorFlow, PyTorch, and scikit-learn, which facilitate the implementation of AI algorithms and frameworks. Additionally, Python's readability and versatility make it suitable for various AI tasks, including machine learning, natural language processing, and computer vision.

The AI For Managers Course is suitablefor professionals in managerial or leadership roles who are interested in understanding and utilizing AI technologies in their organizations. Executives, project managers, business analysts, and decision-makers can benefit from this course.

There are various job roles and career paths within the field of AI, including:

  • AI Engineer/Developer: Responsible for designing, developing, and implementing AI solutions and algorithms.
  • Data Scientist: Analyzes complex data sets to extract insights and develop predictive models using AI techniques.
  • Machine Learning Engineer: Develops and deploys machine learning models and algorithms for specific applications.
  • AI Research Scientist: Conducts research to advance AI technologies and develop innovative algorithms.
  • AI Consultant: Provides expert advice and guidance on implementing AI strategies and solutions for businesses.
  • AI Project Manager: Oversees AI projects, manages teams, and ensures successful implementation and delivery of AI initiatives.
  • AI Ethicist: Focuses on the ethical considerations and implications of AI technologies and develops guidelines for responsible AI usage.
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FAQ’S OF ARTIFICIAL INTELLIGENCE TRAINING IN FARIDABAD

DataMites is a preferred choice for Artificial Intelligence courses in Faridabad due to several reasons:

  • Experienced Faculty: DataMites has industry practitioners and subject matter experts as instructors, providing valuable insights and practical knowledge.
  • Practical Approach: The courses focus on hands-on learning, with projects and case studies that help participants apply their knowledge in real-world scenarios.
  • Industry-Relevant Curriculum: The curriculum is designed based on industry requirements, ensuring participants learn the latest advancements and techniques in AI.
  • Placement Assistance: DataMites offers placement assistance, helping students connect with job opportunities in the AI field.

Eligibility criteria for an Artificial Intelligence Certification Training in Faridabad may vary depending on the specific program. Generally, individuals with backgrounds in computer science, engineering, mathematics, or related fields are eligible to enroll.

Learning Artificial Intelligence in Faridabad is significant due to the increasing demand for AI professionals across industries. It equips individuals with valuable skills sought after in the job market, opens up career opportunities, and allows them to contribute to technological advancements using AI.

Obtaining an Artificial Intelligence Certification in Faridabad is important as it validates one's knowledge and skills in AI. It adds credibility to their profile, enhances job prospects, and demonstrates a commitment to continuous learning and professional development in the field.

DataMites offers various certifications in Artificial Intelligence, including AI Engineer Certification, Certified NLP Expert Certification, AI Expert Certification, AI Foundation Certification, and AI for Managers Certification.

The duration of the Artificial Intelligence course in Faridabad provided by DataMites may vary depending on the specific course chosen. The course duration can range from one month to one year, offering flexibility to accommodate different schedules and preferences. DataMites provides training sessions on both weekdays and weekends, allowing participants to choose a schedule that suits their availability and learning needs.

Individuals can acquire knowledge in the field of Artificial Intelligence through self-study using online resources, textbooks, research papers, and tutorials. They can also enroll in AI courses and training programs, pursue degree or diploma programs in AI or related fields, attend workshops and conferences, and engage in practical projects and competitions to gain hands-on experience.

The AI Engineer Course in Faridabad offered by DataMites aims to equip individuals with the skills and knowledge required to become proficient AI engineers. It covers various aspects of AI, including machine learning, deep learning, natural language processing, computer vision, and AI deployment techniques. The course prepares participants to build and deploy AI models in real-world scenarios.

The Certified NLP Expert course in Faridabad offered by DataMites focuses on Natural Language Processing (NLP), a subfield of AI. The course covers fundamental NLP concepts, text preprocessing, sentiment analysis, named entity recognition, topic modeling, language generation, and neural network-based NLP models. It trains individuals in NLP techniques and their practical applications.

The Artificial Intelligence for Managers Course in Faridabad offered by DataMites covers topics such as AI basics, machine learning, deep learning, natural language processing, computer vision, AI implementation challenges, ethical considerations, and AI project management. It provides managers with the necessary knowledge to make informed decisions regarding AI adoption, implementation, and leveraging AI technologies for business growth.

The AI Foundation Course in Faridabad at DataMites provides a comprehensive introduction to AI. It covers the basics of AI, machine learning, and deep learning. The course content includes an overview of AI, supervised and unsupervised learning, neural networks, deep learning algorithms, model evaluation, and deployment techniques. The course establishes a strong foundation in AI concepts and techniques.

The Flexi-Pass feature available at DataMites allows participants to attend training sessions at their convenience. It offers flexibility in scheduling by providing multiple batch options. This feature ensures that individuals can balance their learning with other commitments and attend classes based on their availability and preference.

The fee for the Artificial Intelligence Training program in Faridabad at DataMites may vary depending on factors such as the specific course selected and the program duration. Generally, the fee for the Artificial Intelligence course in Faridabad ranges from INR 60,795 to INR 154,000.

DataMites offers a range of certifications in the field of Artificial Intelligence, including prestigious certifications from renowned organizations such as IABAC (International Association of Business Analytics Certifications), JAINx, and NASSCOM FutureSkills Prime. These certifications hold significant value in the industry and are highly respected. Completing the Artificial Intelligence training at DataMites provides participants with the opportunity to earn these esteemed certifications, enhancing their professional credibility and marketability in the AI field. These certifications serve as a validation of their skills and knowledge in Artificial Intelligence, distinguishing them in the competitive job market.

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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