Mastering Data Insights with Advanced Data Science Certification
Advanced Data Science Certification serves as a guiding light for data professionals making their way through the complexities of this dynamically changing landscape. This credential covers concepts such as machine learning, big data analytics, and predictive modelling in depth to arm its participants with skills necessary to succeed in the world of data. Advanced Data Science Certification in Japan is a globally recognized certification that demonstrates knowledge of leading-edge techniques and tools needed to extract actionable insights from complex datasets. With a focus on practical use cases and relevance, certified individuals can become potential candidates in various industries ranging from banking to health care. Certification in Advanced Data Science can boost one's career prospects and lets individuals stay ahead of others into new career horizons.
The Essential Role of Certified Advanced Data Scientists
Certified Advanced Data Scientists are valuable assets in the data-centric world. They ensure correct analysis, decision-making based on facts, and effective utilization of information. Additionally, these professionals leverage their skills to enable organizations to understand valuable insights, reduce wastefulness and encourage innovation. Moreover, they practice the best ways to prevent common errors or misinterpretation of data thereby creating a culture of practicalizing of decisions by data and strategic growth. Organizations that invest in Certified Data Science Experts have a competitive edge over others as they guarantee endurance and long-term success in a challenging the business environment.
Advanced Data Science Training and Certification Exam Overview
Advanced Data Science Training is a four-day program that covers everything needed to succeed in the industry of data science. Advanced Data Science Training in Japan is an all-in-one training program designed to teach participants the most important skills and knowledge in this field. It has been developed for professionals such as business analysts, data scientists, data analysts and IT professionals associated with Data Science. Individuals will be trained on machine learning algorithms, big data technologies and how to visualize data. It is facilitated by experienced trainers with industry experience which makes it easy for participants to understand and relate with the content being taught. The course is followed by a final assessment which must be covered within the specified duration. This ensures that professionals have properly understood everything and they are ready for any real-world challenges ahead.
Corporate Group Training
- Customized Training
- Live Instructor-led
- Onsite/Online
- Flexible Dates
Advanced Data Science Exam Details | |
Exam Name | Advanced Data Science Certification |
Exam Format | Multiple choice, Subjective questions |
Total Questions | 20 Questions |
Passing Score | 70% |
Exam Duration | 2 hours |
Key Features of Advanced Data Science Certification Training in Japan
Enrollment in Advanced Data Science Training in Japan offered by Unichrone is designed to equip data professionals with the necessary expertise and abilities to thrive in the contemporary world of big data. Emphasizing the application of concepts and case studies, this course offers a variety of flexible learning options including live online instructor-led classes and in-classroom corporate group training for different learning preferences and organization needs. These include machine learning, big data analytics as well as predictive modelling among others which are advanced subjects covered during this training. The certification earned upon completion is globally recognized. Certification affirms their technical knowledge on how to further advance their career paths in this cutthroat discipline of data science. Advanced-Data Science Training in Japan provides ongoing support from our dedicated team which ensures learners have enough courage to work on any complex problem related to data with confidence.
- 4 Day Interactive Instructor –led Online Classroom or Group Training in Japan
- Course study materials designed by subject matter experts
- Mock Tests to prepare in a best way
- Highly qualified, expert & accredited trainers with vast experience
- Enrich with Industry best practices and case studies and present trends
- Advanced Data Science Training Course adhered with International Standards
- End-to-end support via phone, mail, and chat
- Convenient Weekday/Weekend Advanced Data Science Training Course schedule in Japan
Advanced Data Science Certification Benefits
Higher Salary
With this renowned credential, aspirants earn higher salary packages when compared to non-certified professionals in the field
Individual accomplishments
Aspirants can look for higher career prospects at an early stage in their life with the most esteemed certification
Gain credibility
Owning the certification makes it easier to earn the trust and respect of professionals working in the same field
Rigorous study plan
The course content is prescribed as per the exam requirements, covering the necessary topics to ace the exam in the first attempt
Diverse job roles
Attaining the certification enhances the spirit of individuals to pursue diverse job roles in the organization
Sophisticated skillset
With this certification, individuals acquire refined skills and techniques required to play their part in an organization
Advanced Data Science Training Course Curriculum
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Module 1: Python for Data Analysis - NumPy
Topics
- · Introduction to NumPy
- · NumPy Arrays
- · Aggregations
- · Computation on Arrays: Broadcasting
- · Comparison, Boolean Logic and Masks
- · Fancy Indexing
- · Sorting Arrays
- · NumPy’s Structured Arrays
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Module 2: Python for Data Analysis – Pandas
Topics
- · Installing Pandas
- · Pandas Objects
- · Data Indexing and Selection
- · Operating on Data in Pandas
- · Handling Missing Data
- · Hierarchical Indexing
- ·Concat and Append
- · Merge and Join
- · Aggregations and Grouping
- · Pivot Tables
- · Vectorized String Operations
- · Working with Time Series
- · Eval() and Query()
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Module 3: Python for Data Visualization – Matplotlib
Topics
- · Overview
- · Object-Oriented Interface
- · Two interfaces
- · Simple Line Plots and Scatter Plots
- · Visualizing Errors
- · Contour Plots
- · Histograms, Binnings and Density
- · Customizing Plot Legends
- · Customizing Color Bars
- · Multiple Subplots
- · Text Annotation
- · Three-Dimensional Plotting
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Module 4: Python for Data Visualization – Seaborn
Topics
- · Installing Seaborn and Load Dataset
- · Plot the Distribution
- · Regression Analysis
- · Basic Aesthetic Themes and Styles
- · Distinguish between Scatter Plots, Hexbin Plots and KDE Plots
- · Use Boxplots and Violin Plots
- · Compare the Use Cases of Swarn Plots, Bar Plots Strip Plots, and Categorical Plots
- · Recall Some of the Use Cases and Features of Seaborn
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Module 5: Machine Learning
Topics
- · Introduction
- · Importance
- · Types
- · How Machine Learning Works?
- · Machine Learning Mathematics
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Module 6: Natural Language Processing
Topics
- · Introduction to NLP
- · NLP and Writing Systems
- · Advantages
- · NLP Applications
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Module 7: Deep Learning
Topics
- · Introduction
- · Importance
- · Working
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Module 8: Big Data
Topics
- · Big Data Analytics
- · State of Practice in Analytics
- · Main Roles for New Big Data Ecosystem
- · Phases of Data Analytics Lifecycle
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Module 9: Working with Data in R
Topics
- · Data Manipulation in R
- · Data Clean Up
- · Reading and Exporting Data
- · Importing Data
- · Charts and Graphs
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Module 10: Regression in R
Topics
- · Regression Analysis
- · Linear Regression
- · Logistic Regression
- · Multiple Regression
- · Normal Distribution
- · Binomial Distribution
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Module 11: Modelling Data
Topics
- · What are Relationships?
- · Viewing Relationships
- · Creating Relationships
- · Cardinality
- · Cross Filter Direction
- · What is DAX?
- · Syntax
- · Functions
- · Row Context
- · Calculated Columns
- · Calculated Tables
- · Measures
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Module 12: Shaping and Combining Data using Power BI
Topics
- · Query Editor
- · Shaping Data and Applied Steps
- · Advanced Editor
- · Formatting Data
- · Transforming Data
- · Combining Data
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Module 13: Interactive Data Visualizations
Topics
- · Page Layout and Formatting
- · Multiple Visualization
- · Creating Charts
- · Using Geographic Data
- · Histograms
- · Power BI Admin Portal
- · Service Settings
- · Desktop Settings
- · Dashboard and Report Settings