ARTIFICIAL INTELLIGENCE CERTIFICATION AUTHORITIES

Artificial Intelligence Course Features

ARTIFICIAL INTELLIGENCE LEAD MENTORS

ARTIFICIAL INTELLIGENCE COURSE FEE IN VIETNAM

Live Virtual

Instructor Led Live Online

VND 55,066,670
VND 33,682,739

  • 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

VND 38,618,180
VND 21,587,739

  • 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

Corporate Training

Customize Your Training


  • Instructor-Led & Self-Paced training
  • Customized Learning Options
  • Industry Expert Trainers
  • Case Study Approach
  • Enterprise Grade Learning
  • 24*7 Cloud Lab

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UPCOMING ARTIFICIAL INTELLIGENCE TRAINING SCHEDULES IN VIETNAM

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 VIETNAM

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 VIETNAM

ARTIFICIAL INTELLIGENCE TRAINING REVIEWS

ABOUT ARTIFICIAL INTELLIGENCE TRAINING IN VIETNAM

Technology's ever-evolving area offers a plethora of intriguing and innovative job prospects. Engineering for Artificial Intelligence (AI) is a rapidly expanding field. It can give you fresh challenges as well as intriguing professional development chances.

“Predicting the future isn’t magic, it’s Artificial Intelligence.”

   -  Dave Waters

AI refers to machines that act in a human-like manner. They are capable of learning and making decisions in the same way as humans are. These machines are capable of seeing, evaluating, and learning from facts and errors in the same way that a human brain does. Artificial intelligence is having an impact on organisations and has even led to advancements in the medical, retail, hospitality, manufacturing, and finance industries.

Artificial Intelligence (AI) has exploded in popularity, and businesses all over the world are implementing it into their processes to improve corporate operations and consumer experience.

Did you know that...

The job openings for artificial intelligence jobs revealed to be over 45,000 in the LinkedIn list of jobs.

Freshers, software professionals, and analytically oriented persons can benefit from Datamites' cost-effective, high-quality, and real-time training courses. In this age of technological explosion, having the knowledge and aptitude to operate rapidly evolving technology is unavoidable. The road has been paved by technology. You have the ability to master a subject if you are well-versed in it.

DataMites is on the verge of becoming India's most prestigious training institute. In India, the United Kingdom, the United States, Saudi Arabia, the United Arab Emirates, South Africa, the Philippines, and other countries, we provide comprehensive training in Artificial Intelligence and related subjects. At DataMites, we're thrilled to have exceeded the 50-thousand-learner mark. The International Association of Business Analytics Certification - IABAC - has given DataMites global recognition. DataMites provides training from subject matter experts that are knowledgeable and skilled in their industries. Our main goal is to mould and shape specialists that can confidently handle the complexities of highly competitive analytics. Are you interested in learning more about Artificial Intelligence?

In today's world, IT utopia is on the rise. Vietnam has a large population of young digital natives with the business acumen and innovative prowess that are the lifeblood of the global tech industry. AI, machine learning, and IoT are saturating the market and strengthening the ecosystem in this tornado of entrepreneurial instability. For decades to come, the city has a plethora of expanding revenue and untapped growth potential.

Vietnam's economy has witnessed remarkable growth in recent years, becoming one of the fastest-growing economies in Southeast Asia. With a GDP of $340 billion, the country has achieved an average annual growth rate of around 6-7%. Vietnam's exports, valued at $340 billion, have been a driving force, with key sectors including electronics, textiles, and agricultural products. Foreign direct investment inflows reached $16 billion. Furthermore, Vietnam's poverty rate has decreased significantly, with only 5.3% of the population living below the poverty line. These statistics demonstrate the robust and dynamic nature of Vietnam's economy.

Artificial Intelligence (AI) is rapidly transforming various industries, making it imperative to recognize the importance of an Artificial Intelligence course. By enrolling in such a course, individuals can acquire the necessary skills and knowledge to harness the power of AI. This enables them to develop innovative solutions, automate processes, and enhance decision-making across sectors like healthcare, finance, and transportation. AI courses provide a comprehensive understanding of machine learning algorithms, natural language processing, and computer vision, empowering learners to create cutting-edge applications that revolutionize the way we live and work.

We provide 6 monthly Artificial Intelligence Courses in Vietnam with both Artificial Intelligence Online Training and Artificial Intelligence Classroom Training that would be imparted within a three-phase learning method. 

Phase 1 = It’s time to get prepared for the course to come, candidates would be provided with self-study videos and books of high quality to enable an excellent grasp of the curriculum as a whole.

Phase 2 = The primary stage of Live Intensive training along with hands-on capstone projects and after the training, you will receive IABAC Artificial Intelligence Certification, a global certification. 

Phase 3 = Projects, Internships and Job ready Program.

Courses we offer in Artificial Intelligence:

  • Artificial Intelligence Engineer - AI engineers are extremely crucial in today's economy, particularly in sectors and verticals where AI technology has already made a substantial influence. AI engineers are in charge of creating new apps and systems that use AI to boost productivity, make better decisions, save expenses, and raise profitability. The course covers Artificial Intelligence Foundations, Machine Learning, Tensorflow 2 X Platform, Core Learning Algorithms, Neural Networks Implementing Deep Neural Networks, Deep Computer Vision - Convolutional Neural Networks, Recurrent Neural Network, Natural Language Processing, Reinforcement Learning, Deep Reinforcement Learning, Generative Adversarial Network (Gan), Deploying Deep Learning Models In The Cloud, and Reinforcement Learning, Deep Reinforcement Learning, Deep Rein (Aws). Our AI Engineer programme lasts six months.

  • Expert in Artificial Intelligence (AI) - Experts in artificial intelligence (AI) design computers to mimic human reasoning. They work on systems that collect data, make judgments, and take action based on that data. Artificial Intelligence Foundation, Machine Learning Foundation, Tensorflow 2. X Platform, Core Learning Algorithms, Neural Networks, Implementing Deep Neural Networks, Deep Computer Vision - Convolutional Neural Networks, Recurrent Neural Networks, Natural Language Processing, Reinforcement Learning, Deep Reinforcement Learning, Generative Adversarial Network (GAN), Natural Language Processing, Reinforcement Learning, Deep Reinforcement Learning, Generative Adversarial Network (GAN The duration of our AI Expert Course will be two months.

  • Artificial Intelligence for Managers - AI for Managers is a course aimed at senior executives and managers who want to apply their AI knowledge at the highest levels of an organisation. AI is faster than humans in crunching numbers, identifying trends, and making data-driven judgments. You may adjust and improve your career prospects and worth to the organisation by learning how to work with AI and using the recommendations it can provide. The duration of our AI for Managers training will be two weeks.

  • Certified Natural Language Processing Expert - Natural language processing (NLP) is a core component of artificial intelligence. The ultimate goal of natural language processing is for computers to comprehend texts and languages in the same way that humans do. The Certified Natural Language Processing Expert course is designed to help you develop and apply the abilities you'll need to apply natural language processing in real-world circumstances. It investigates the many options for implementing Natural Language Processing's potential. The programme will last three months.

  • Artificial Intelligence Foundation - This curriculum is for people who have little or no experience with AI, computer science, or Artificial Intelligence, and it does not require any programming knowledge. Each course is meant to give students a practical understanding of AI's fundamental concepts, as well as its many applications and use cases in a variety of industries. Whether you have a technical background or not, this course is for you. No prior knowledge of AI is required, and no programming abilities are required. It's intended to provide you with a thorough grasp of AI, its applications, and real-world examples from a variety of industries. Machine learning, deep learning, and neural networks are all terminology you'll be familiar with. The AI Foundation Course will last two months.

Datamites offers flexible learning options starting from Artificial Intelligence Classroom Courses, Artificial Intelligence Online Courses to Exceptional Recorded Sessions. The global Artificial Intelligence (AI) market size is expected to gain momentum by reaching USD 360.36 billion by 2028 while exhibiting a CAGR of 33.6% between 2021 to 2028.

DataMites Artificial Intelligence Course Fee in Vietnam ranges from 5,692,748 VDN to 16,823,819 VDN as per your preferred choice of learning. You can always check in on your desired course and find out the course fee for the same.

DataMites Highlights:

  • Global Recognition - IABAC Accreditation

  • Expert Training - Elite Faculty with relevant research and coaching experience

  • Comprehensive Training 

  • Real-time Projects and Internships

  • 100% Job Ready Assistance

Due to increased rivalry in the corporate world, innovations in consumer interaction have been necessary for recent years. As a result, businesses are investing in technology to provide their customers with a better experience at a lower cost. As a result, AI technology is now being used to provide consumers with individualised and specialised services in real-time.

Did you know about Artificial Intelligence?

By 2026, the US Bureau of Labor Statistics estimates that there will be over 11.6 million job openings in Artificial Intelligence and analytics!

Artificial intelligence has long been a popular term in computer science and the subject of computers, and it has recently grown in popularity as a result of recent developments in the fields of artificial intelligence and machine learning. Machine learning refers to the branch of artificial intelligence in which robots are in charge of completing daily tasks and are thought to be smarter than humans. Robotics and IoT device integration have elevated machine thinking and labour to a new level, allowing machines to outsmart humans in terms of cognitive capacities and intelligence. They have been observed to learn, adapt, and perform considerably more quickly than humans are taught to do. 

If you're interested in working in the field of artificial intelligence, DataMites Artificial Intelligence Training in Vietnam is the finest option. This could be the key to your success!

DataMites also provides training for Certified Data Analyst, Machine Learning, Deep Learning, Python, IoT, Python for Data Science, and the entire Data Science courses.

DESCRIPTION OF ARTIFICIAL INTELLIGENCE COURSE IN VIETNAM

Artificial intelligence uses computers and technology to simulate the human mind's problem-solving and decision-making abilities.

The term "artificial intelligence" was introduced for the first time by John McCarthy, a professor emeritus of computer science at Stanford.

Artificial Intelligence (AI) is a discipline of computer science that focuses on the creation of intelligent machines that think and function in the same way that people do. 

  • Robotics

  • Healthcare

  • Data Security

  • Gaming

  • Finance

  • Digital Media, Social Media

  • Travel

  • Automotive Industry

  • Customer Service

  • Facial Recognition

  • AI has enormous promise.

  • Effortlessness in the workplace

  • There would be few to no inaccuracies in the results.

  • AI reduces the time it takes to complete a task. It allows for multitasking and lightens the demand for current resources.

  • AI allows previously complicated activities to be completed without incurring significant costs.

  • AI is available 24 hours a day, seven days a week, with no downtime.

  • AI improves the talents of people with varied abilities.

  • AI has large market potential and may be used in a variety of industries.

  • AI makes decision-making easier by making it faster and smarter.

Natural language processing (NLP) is a subject of computer science—specifically, a branch of artificial intelligence (AI)—concerning the ability of computers to understand text and spoken words in the same manner that humans can.

Artificial intelligence is frequently utilised to present individuals with customised recommendations based on their prior searches and purchases, as well as other online activities. In business, AI plays a critical role in product optimization, inventory planning, and logistics, among other things.

Because the majority of industry verticals are leveraging AI and machine learning for a brighter tomorrow and producing many career opportunities as a result. Because of recent advancements such as intelligent voice assistants, self-driving cars, robotic process automation, and so on, ML and AI have recently gained traction. All of this has swept the globe, and everyone now wants to understand more about these technologies. Artificial Intelligence workers are earning more money.

Anyone interested in learning Artificial Intelligence, whether a newbie or a professional, can enrol. Part-time or external Artificial Intelligence programmes are available for engineers, marketing professionals, software and IT professionals. Regular Artificial Intelligence courses need the completion of basic high school level studies.

  • Big Data Engineer

  • Business Intelligence Developer

  • Data scientist

  • Machine learning engineer

  • Research Scientist

  • AI Data Analyst

  • Product Manager

  • AI Engineer

  • Robotic Scientist

  • Data Analyst

Learning Artificial Intelligence will benefit from skills such as computer programming, statistics and probability, data modelling, data validation, and design. Non-technical skills such as critical thinking, a curious mentality, and a passion for math and science are required.

Yes, Artificial Intelligence is difficult, but nothing is impossible if you set your mind to it. It is entirely dependent on the individual; if you are interested, you will be able to do the task quickly. Artificial Intelligence has a brighter future ahead of it.

Microsoft Azure AI Platform, Google Cloud AI Platform, IBM Watson, Infosys Nia, Dialog Flow, and BigML are some of the greatest AI software development tools.

Artificial Intelligence now outperforms practically every industry on the planet. There isn't a single industry on the earth these days that isn't reliant on data. Artificial Intelligence has thus become a source of energy for businesses. Artificial intelligence can be used in a variety of fields, including travel, healthcare, sales, credit and insurance, marketing, social media, automation, and much more.

Jobs in AI and machine learning have increased by about 75% in the last four years and are expected to continue to rise. Getting a job in machine learning is a great way to get a high-paying job that will be in demand for decades. MarketsandMarkets expects the global artificial intelligence (AI) market to develop at a CAGR of 39.7% from USD 58.3 billion in 2021 to USD 309.6 billion in 2026, according to MarketsandMarkets.

A month's salary for an Artificial Intelligence Developer in Vietnam is normally around 19,800,000 VND. Salaries range from 10,100,000 VND to 30,500,000 VND (lowest to highest) - (Salaryexplorer.com)

Artificial Intelligence has a wide range of uses and applications. Companies all over the world are on the lookout for Artificial Intelligence experts that can add value to their organisations. Artificial Intelligence credentials can help you advance in your job in today's technologically advanced environment.

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FAQ’S OF ARTIFICIAL INTELLIGENCE TRAINING IN VIETNAM

DataMites renders Artificial Intelligence Training in:

  • Artificial Intelligence Engineer

  • Artificial Intelligence Expert

  • Certified NLP Expert

  • Artificial Intelligence for Managers

  • Artificial Intelligence Foundation

The Duration of the Artificial Intelligence course in Vietnam varies from 6 months to 2 weeks depending on the course you choose to study. Training sessions are imparted on weekdays and weekends. You can choose any as per your availability.

Artificial Intelligence is a highly sought-after topic of study with high-paying job opportunities. Aspirants can enrol in our Artificial Intelligence Course at Datamites, where we will provide in-depth instruction for their future careers.

An artificial intelligence engineer is a person who builds models for AI-based applications using classic machine learning techniques such as natural language processing and neural networks.

An AI engineer creates AI models that use machine learning algorithms and deep learning neural networks to derive business insights that may be used to make large-scale business decisions. They use a variety of tools and strategies to process data and build and manage AI systems.

An Artificial Intelligence Engineer is a computer scientist whose goal is to create intelligent algorithms that can learn, analyse, and anticipate future occurrences. Their mission is to develop machines that can reason like a human brain. The DataMites Artificial Engineer training provides the knowledge and abilities needed to succeed as an AI Engineer. Specifically, the course discusses how to use deep learning, machine learning, computer vision, and natural language processing to solve complicated problems.

Artificial Intelligence (AI) is a chance. Every company is attempting to take advantage of the opportunities. The Certified Artificial Intelligence Expert discusses how data science may be integrated into human resource management. The main focus of the Certified Artificial Intelligence Expert course is on applying artificial intelligence knowledge to organisational operations.

Artificial Intelligence for Managers is primarily concerned with exploiting AI knowledge at the executive level of a company. The degree of AI's employability differs at different levels, and as it progresses upwards, it proves to be at its finest.

The Certified Natural Language Processing Expert course is designed to help you develop and apply the abilities you'll need to apply natural language processing in real-world circumstances. It investigates the many options for implementing Natural Language Processing's potential.

The AI Foundation course is a beginner's course aimed to help newcomers get started in the field of artificial intelligence. Whether you have a technical background or not, this course is for you. No prior knowledge of AI is required, and no programming abilities are required. It's intended to provide you with a thorough grasp of AI, its applications, and real-world examples from a variety of industries. Machine learning, deep learning, and neural networks are all terminology you'll be familiar with.

  • Datamites™ is the global institute for Artificial Intelligence accredited by the International Association of Business Analytics Certification (IABAC).

  • We have more than 25,000 students enrolled in the courses we offer.

  • We provide a three-step learning method. In Phase 1, self-study videos and books will be provided to the candidates to help them get adequate knowledge about the syllabus. Phase 2 is the primary phase of intensive live online training. And in the third phase, we will release the projects and placements.

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

  • After the training, you will receive the IABAC certification which is a global certification.

  • After completing your training, you will get the chance to do an internship with AI company Rubix, a global technology company.

The fees for the Artificial Intelligence Course will range from 3,142,297 VDN to 954,622,950 VDN in Vietnam. It all depends on the course and mode of training you choose.

Datamites does provide classroom training, but only in Bangalore. We would be pleased to host one in other locations, ON-DEMAND of the applicants as according to the availability of other candidates from the exact location.

We are determined to provide you with trainers who are certified and highly qualified with decades of experience in the industry and well versed in the subject matter.

Our Flexi-Pass for Artificial Intelligence training will allow you to attend sessions from Datamites for a period of 3 months related to any query or revision you wish to clear.

We will issue you an IABAC® certification that provides global recognition of relevant skills.

Of course, after your course is completed, we will issue you a Course Completion Certificate.

Yes. Photo ID proofs like a National ID card, Driving license etc. are needed for issuing the participation certificate and booking the certification exam as required.

You don't need to worry about it. Just get in touch with your instructors regarding the same and schedule a class as per your schedule.

In the case of Artificial Intelligence Online Training in Vietnam, each session will be recorded and uploaded so that you can easily learn what you missed at your own pace and comfort.

Yes, a free demo class will be provided to you to give you a brief idea of ??how the training will be done and what will be involved in the training.

Yes, we have a dedicated Placement Assistance Team (PAT) who will provide you with placement facilities after the completion of the course.

The DataMites Placement Assistance Team (PAT) assists applicants in completing all of the necessary processes to begin their Artificial Intelligence career. PAT offers a variety of services, including: -

1. Make a job connection

2. Creating a Resume

3 Mock interviews with industry professionals

4. Discuss Questions for the interview

The DataMites Placement Assistance Team (PAT) holds career coaching sessions for applicants with the goal of assisting them in recognising the purpose they will serve once they enter the corporate sector. Students are guided by industry experts through the numerous options accessible in the Artificial Intelligence career, allowing applicants to have a thorough image of their options. They will also learn about the many hurdles they are likely to meet as a newcomer to the industry and how to overcome them.

Learning Through Case Study Approach

Theory → Hands-on → Case Study → Project → Model Deployment

Yes, of course, it is important that you make the most of your training sessions. You can of course ask for a support session if you need any further clarification.

We accept payment through;

  • Cash

  • Net Banking

  • Check

  • Debit Card

  • Credit Card

  • PayPal

  • Visa

  • Master card

  • American Express

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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