Know more about Advanced Data Science Certification
Advanced Data Science Certification is an attestation providing in-depth knowledge of advanced topics, and statistical modeling, machine learning, and data visualization techniques in detail. It equips individuals with the caliber to implement various modeling data in Power BI data models. Advanced Data Science Certification in Setagaya Japan sheds light on data analysis using Python. It provides an overview for individuals about installing pandas and its operation. Therefore, having this certification can help a professional clear the ambiguities of different phases of the data analytics life cycle. Definitely, the attestation of Advanced Data Science can impact crucially on the professional life of an individual, as it is a globally admired validation of knowledge in Advanced Data Science.
A Guide on Advanced Data Science Exam
Advanced Data Science Exam in Setagaya is purposeful in analyzing the profoundness a professional has on tackling challenges of complex data sets. It is compulsory to take Data Science Exam after the course completion. Course provides all relevant knowledge on the topics related to Advanced-level Data Science, which helps the aspirant crack the exam with less effort. The exam is conducted for 120 minutes. There will be twenty questions that candidates must answer, which are objective types of questions. Exam is course-related, and candidates must have a thorough consciousness of all predominant topics, of course.
Understand more about Advanced Data Science Training
Advanced Data Science Training in Setagaya provides a thorough knowledge of advanced data science, enhancing expertise in individuals. Data Science Program adopts personalized teaching methodologies to improve Data Science learning. This enables candidates to attain extensive knowledge of machine learning and big data analytics. Furthermore, Data Science Certification Course provides knowledge on deep learning, its importance and working. It pertains to data manipulation in R and regression analysis. Moreover, training helps aspirants with advanced consciousness in modeling data and creating relationships. Additionally, online and offline sessions bestow detailed information on multiple visualizations and creating charts.
Corporate Group Training
- Customized Training
- Live Instructor-led
- Onsite/Online
- Flexible Dates
Advanced Data Science Exam Details in Setagaya | |
Exam Name | Advanced Data Science Certification |
Exam Format | Multiple choice |
Total Questions | 20 Questions |
Passing Score | 70% |
Exam Duration | 2 hours |
Key Features of Advanced Data Science Certification Training in Setagaya Japan
Unichrone is offering reliable and well-organized training on Advanced Data Science. We assist candidates with online and in-classroom training sessions in Setagaya. In addition, there will be group training for aspirants, which accelerates their learning. Moreover, we cater industry-oriented course materials and mock quizzes that provide persistent practice and learning for professionals on Data Science topics on an advanced level. Course helps the candidates to improve their knowledge in machine learning mathematics and NLP applications. Moreover, Advanced Data Science Certification offered by Unichrone is intended to provide awareness to the aspirant about ethical considerations in data science and its real-time applications. It enhances the skills in Python for data analysis and visualization with utmost importance. Our course instructors are well averse to the vital needs of industry. We support our learners till the end of their course. More than that, we provide extensive networking opportunities for aspirants to accomplish a competitive edge in the industry. There will be a thorough support in the career advancement of professionals after the course completion.
- 4 Day Interactive Instructor –led Online Classroom or Group Training in Setagaya Japan
- Course study materials designed by subject matter experts
- Mock Tests to prepare in a best way
- Highly qualified, expert trainers with vast industrial 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 Setagaya 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