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Become an expert Artificial Intelligence Engineer by enrolling in Master’s in Artificial Intelligence in Japan from Intellipaat. Our instructors with 12+ years of experience will teach you all about Data Science, Python, ANNs, etc. This MS in Artificial Intelligence course is well-designed with 24/7 support and live projects so that you can gain practical expertise.
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Course PreviewAs a learner, you will soon be able to master different concepts such as Deep Learning with TensorFlow, R programming, Tableau, Data Science, Python coding, making use of Watson Assistant to build chatbots, Business Analytics, etc. through this AI Master’s in Japan program.
No. We do not have any prerequisites for enrollment in this master’s course in Artificial Intelligence.
| Information | Value |
| Average Salary of AI Professionals in Japan | ¥4,083,000/year – PayScale |
| Projected Economic Return from AI Technologies | ¥121 trillion by 2045 – The Government of Japan |
| Number of AI Job Listings in Japan | Over 450 jobs listed – Shine |
Please note that the salary figure is provided by PayScale and represents the average annual salary for AI professionals in Japan. The projected economic return is an estimate from the Government of Japan for the year 2045, and the number of job listings is based on data from Shine.
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57% Average Salary Hike
$1,14,000 Highest Salary
12000+ Career Transitions
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*Past record is no guarantee of future job prospects
Develop strategies on technologies, frameworks, and infrastructure that could help in creating AI solutions.
Assess and validate the Artificial Intelligence models using tuning and model fit testing.
Develop robust optimization algorithms for numerous applications built on Artificial Intelligence.
Use Machine Learning tools and techniques to create statistical models consisting of large volumes of data.
Scale and prototype the latest Machine Learning and Artificial Intelligence solutions in the cloud environment in order to meet the business requirements.
Artificial Intelligence using Python
Data Science with R
Machine Learning
Business Analytics
Business Intelligence
TSA
SVM
Neural Networks
Graph visualization
Keras
Deep Learning with TensorFlow
Natural Language Processing
Excel
Tableau
$562
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42 Hours 12 Module
PreviewModule 01 – Python Environment Setup and Essentials
Module 02 – Python language Basic Constructs
Module 03 – OOP concepts in Python
Module 04 – Database connection
Module 05 – NumPy for mathematical computing
Module 06 – SciPy for scientific computing
Module 07 – Matplotlib for data visualization
Module 08 – Pandas for data analysis and machine learning
Module 09 – Exception Handling
Module 10 – Multi Threading & Race Condition
Module 11 – Packages and Functions
Module 12 – Web scraping with Python
32 Hours 9 Module
PreviewModule 01 – Introduction to Machine Learning
Module 02 – Supervised Learning and Linear Regression
Module 03 – Classification and Logistic Regression
Module 04 – Decision Tree and Random Forest
Module 05 – Naïve Bayes and Support Vector Machine (self-paced)
Module 06 – Unsupervised Learning
Module 07 – Natural Language Processing and Text Mining (self-paced)
Module 08 – Introduction to Deep Learning
Module 09 – Time Series Analysis (self-paced)
32 Hours 13 Module
PreviewModule 01 – Introduction to Deep Learning and Neural Networks
Module 02 – Multi-layered Neural Networks
Module 03 – Artificial Neural Networks and Various Methods
Module 04 – Deep Learning Libraries
Module 05 – Keras API
Module 06 – TFLearn API for TensorFlow
Module 07 – Dnns (deep neural networks)
Module 08 – Cnns (convolutional neural networks)
Module 09 – Rnns (recurrent neural networks)
Module 10 – Gpu in deep learning
Module 11 – Autoencoders and restricted boltzmann machine (rbm)
Module 12 – Deep learning applications
Module 13 – Chatbots
20 Hours 6 Module
PreviewModule 01 – Overview of Natural Language Processing and Text Mining
Module 02 – Text Mining, Cleaning, and Pre-processing
Module 03 – Text Classification
Module 04 – Sentence Structure, Sequence Tagging, Sequence Tasks, and Language Modeling
Module 05 – Introduction to Semantics and Vector Space Models
Module 06 – Dialog Systems
42 Hours 15 Module
PreviewModule 01 – Introduction to Data Science with R
Module 02 – Data Exploration
Module 03 – Data Manipulation
Module 04 – Data Visualization
Module 05 – Introduction to Statistics
Module 06 – Machine Learning
Module 07 – Logistic Regression
Module 08 – Decision Trees and Random Forest
Module 09 – Unsupervised Learning
Module 10 – Association Rule Mining and Recommendation Engines
Module 11 – Introduction to Artificial Intelligence
Module 12 – Time Series Analysis
Module 13 – Support Vector Machine (SVM)
Module 14 – Naïve Bayes
Module 15 – Text Mining
24 Hours 23 Module
PreviewModule 01 – Entering Data
Module 02 – Referencing in Formulas
Module 03 – Name Range
Module 04 – Understanding Logical Functions
Module 05 – Getting started with Conditional Formatting
Module 06 – Advanced-level Validation
Module 07 – Important Formulas in Excel
Module 08 – Working with Dynamic table
Module 09 – Data Sorting
Module 10 – Data Filtering
Module 11 – Chart Creation
Module 12 – Various Techniques of Charting
Module 13 – Pivot Tables in Excel
Module 14 – Ensuring Data and File Security
Module 15 – Getting started with VBA Macros
Module 16 – Ranges and Worksheet in VBA
Module 17 – IF condition
Module 18 – Loops in VBA
Module 19 – Debugging in VBA
Module 20 – Dashboard Visualization
Module 21 – Principles of Charting
Module 22 – Getting started with Pivot Tables
Module 23 – Statistics with Excel
30 Hours 13 Module
PreviewModule 01 – Introduction to Data Visualization and The Power of Tableau
Module 02 – Architecture of Tableau
Module 03 – Charts and Graphs
Module 04 – Working with Metadata and Data Blending
Module 05 – Advanced Data Manipulations
Module 06 – Working with Filters
Module 07 – Organizing Data and Visual Analytics
Module 08 – Working with Mapping
Module 09 – Working with Calculations and Expressions
Module 10 – Working with Parameters
Module 11 – Dashboards and Stories
Module 12 – Tableau Prep
Module 13 – Integration of Tableau with R
Projects will be a part of your Artificial Intelligence Master’s program to consolidate your learning. It will ensure that you have real-world experience in AI.
The course in Japan is created and delivered to help you get the top jobs in the world. The course includes real-world projects that are extremely valuable. The course completion certificate from Intellipaat is awarded upon successfully completing the projects.
This Artificial Intelligence Master’s course is designed for clearing the following industry certifications:
Land Your Dream Job Like Our Alumni
Intellipaat provides the best Artificial Intelligence Master’s Programs in Japan that gives you all the skills needed to work in the domains of AI, Machine Learning, Deep Learning, Data Science with R Statistical computing and Python to give the professionals an added advantage. Upon the completion of the training, you will be awarded the Intellipaat Artificial Intelligence Engineer certification.
You will be working on real-time projects and step-by-step assignments that have high relevance in the corporate world, and the curriculum is designed by industry experts. Upon the completion of the Master’s Program in Artificial Intelligence, you can apply for some of the best jobs in top MNCs around the world at top salaries. Intellipaat offers lifetime access to videos, course materials, 24/7 support and course material upgrading to the latest version at no extra fee. Hence, it is clearly a one-time investment.
Intellipaat has been serving AI and ML enthusiasts from every corner of Japan. You can be living in any country, be it Tokyo, Yokohama, Osaka, Nagoya, Sapporo, Fukuoka, Kobe, Kawasaki, Kyoto, Saitama, Hiroshima, Sendai, Chiba, or anywhere. You can have full access to the best Artificial Intelligence Master’s programs in the world sitting at home or office 24/7.
Intellipaat offers query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail yourself of email support for all your queries. We can also arrange one-on-one sessions with our support team If your query does not get resolved through email. However, 1:1 session support is given for 6 months from the start date of your course.
Intellipaat provides placement assistance to all learners who have completed the training and moved to the placement pool after clearing the PRT (Placement Readiness Test). More than 500+ top MNCs and startups hire Intellipaat learners. Our alumni work with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.
No, our job assistance is aimed at helping you land your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final hiring decision will always be based on your performance in the interview and the requirements of the recruiter.
