Data Science 360 Degree Course

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Curriculum For Data Science 360 Degree Course

  • icons-carri22 Module 1: Introduction to Data Visualization and Power of Tableau

    In this module the candidate will learn about Data Visualization, Comparison benefits against reading raw numbers, Real use cases from various business domains, Examples of using Tableau, installing Tableau, Tableau interface, Connecting to Data source, Tableau data types and Data preparation
    • Comparison and benefits against reading raw numbers
    • Real use cases from various business domains
    • Some quick and powerful examples using Tableau without going into the technical details of Tableau
    • Installing Tableau
    • Tableau interface
    • Connecting to Data Source
    • Tableau data types
    • Data preparation
    • Quiz Module 1
  • icons-carri22 Module 2: Architecture of Tableau

    In this module the candidate will learn about Architecture of Tableau, which includes learning of the installation, Desktop Architecture and Interface of Tableau, how to start with Tableau and the ways to share and export the work done in Tableau. The candidate will also be provided with a few Hands-on exercises, which will enhance the understanding of the Tableau
    • Installation of Tableau
    • Desktop Architecture of Tableau
    • Interface of Tableau (Layout, Toolbars, Data Pane, Analytics Pane, etc.)
    • How to start with Tableau
    • The ways to share and export the work done in Tableau
    • Quiz Module 2
  • icons-carri22 Module 3: Working with Metadata and Data Blending

    In this module the candidate will learn working with Metadata and Data Blending, which includes understanding Connection to Excel, Cubes and PDFs, Management of the Metadata, preparation of Data, Joins and Unions , and how to deal with NULL Values, Cross- database joining, data extraction etc. The candidate will also be provided with Hands-on Exercises which will enhance the understanding of the candidate, of the topic and its working
    • Connection to Excel
    • Cubes and PDFs
    • Management of metadata and extracts
    • Data preparation
    • Joins (Left, Right, Inner, and Outer) and Union
    • Dealing with NULL values, cross-database joining, data extraction, data blending, refresh extraction, incremental extraction, how to build extract, etc.
    • Quiz Module 3
  • icons-carri22 Module 4: Creation of Sets

    In this module the candidate will learn about Creation Sets, in which you will learn how to Mark, Highlight, Sort, Group, and use Sets, understand what are Constant Sets, Computed Sets, Bins etc. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned
    • Mark, highlight, sort, group, and use sets (creating and editing sets, IN/OUT, sets in hierarchies)
    • Constant sets
    • Computed sets, bins, etc
    • Quiz Module 4
  • icons-carri22 Module 5: Working with Filters

    In this module the candidate will learn about Filters, how to work with Filters, Filtering Continuous Dates, Dimensions and Measures, create folders in Tableau, sorting in Tableau, Filtering in Tableau and the order of Operations, types of Sorting and Filters. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned
    • Filters (Addition and removal)
    • Filtering continuous dates, dimensions, and measures
    • Interactive Filters, marks card, and hierarchies
    • How to create folders in Tableau
    • Sorting in Tableau
    • Types of sorting
    • Filtering in Tableau
    • Types of filters
    • Filtering the order of operations
    • Quiz Module 5
  • icons-carri22 Module 6: Organizing Data and Visual Analytics

    In this module the candidate will learn about Visual Analytics and Organizing Data, in which the candidate will learn about usage of Formatting Pane and how to Format Data using Labels and Tooltips, Edit Axes and annotations, K-means cluster analysis, Trend and Reference lines, Visual Analytics and Forecasting, Confidence Interval, Reference lines and Bands. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working
    • Using Formatting Pane to work with menu, fonts, alignments, settings, and copy-paste
    • Formatting data using labels and tooltips
    • Edit axes and annotations
    • K-means cluster analysis
    • Trend and reference lines
    • Visual analytics in Tableau
    • Forecasting, confidence interval, reference lines, and bands
    • Quiz Module 6
  • icons-carri22 Module 7: Working with Mapping Preview

    In this module the candidate will learn about Mapping Preview, which includes Working on Coordinate points and the background image, Plotting Longitude and Latitude, editing unrecognized Location, Customizing Geocoding, Maps etc., Map visualization, Custom territories, Map box WMS map and creating Map projects in Tableau and Dual Axes Maps. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working
    • Working on coordinate points
    • Plotting longitude and latitude
    • Editing unrecognized locations
    • Customizing geocoding, polygon maps, WMS: web mapping services
    • Working on the background image, including add image
    • Plotting points on images and generating coordinates from them
    • Map visualization, custom territories, map box, WMS map
    • How to create map projects in Tableau
    • Creating dual axes maps and editing locations
    • Quiz Module 7
  • icons-carri22 Module 8: Working with Calculations and Expressions

    In this module the candidate will learn about Calculations and functions in Tableau, LOD expressions, aggregation and Replication with LOD expressions, Nested LOD expressions, Levels of details, Quick table calculations, Creation of calculated fields and Predefined calculations and validation
    • Calculation syntax and functions in Tableau
    • Various types of calculations, including Table, String, Date, Aggregate, Logic, and Number
    • LOD expressions, including concept and syntax
    • Aggregation and replication with LOD expressions
    • Nested LOD expressions
    • Levels of details: fixed level, lower level, and higher level
    • Quick table calculations
    • The creation of calculated fields
    • Predefined calculations
    • How to validate
    • Quiz Module 8
  • icons-carri22 Module 9: Working with Parameters Preview

    In this module the candidate will learn about Parameters, creating and its calculations, using Parameters with calculations Column and chart selection parameters, usage of Parameters in filter sessions, calculated fields and in reference line. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working
    • Creating parameters
    • Parameters in calculations
    • Using parameters with filters
    • Column selection parameters
    • Chart selection parameters
    • How to use parameters in the filter session
    • How to use parameters in calculated fields
    • How to use parameters in the reference line
    • Quiz Module 9
  • icons-carri22 Module 10: Charts and Graphs

    In this topic the candidate will learn about Charts and Graphs, such as, Dual axes graphs, Histograms, Single and dual axes, Box plot, Charts; motion, pie , bar etc., Maps: tree and heat maps, Market Based Analysis and text and highlighted table. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working
    • Dual axis graphs
    • Histograms
    • Single and dual axis
    • Box plot
    • Charts: motion, Pareto, funnel, pie, bar, line, bubble, bullet, scatter, and waterfall charts
    • Maps: tree and heat maps
    • Market basket analysis (MBA)
    • Using Show me
    • Quiz Module 10
  • icons-carri22 Module 11: Dashboards and Stories

    In this module the candidate will learn about Dashboard, which includes topics such as, building and formatting, best practices for making creative dashboard, creating stories, updating the story points, Adding annotations with descriptions, Highlight actions, URL actions, types of Joins, Tableau field types, Saving as well as publishing data source, difference between Live and Extract connection and various file types. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working.
    • Building and formatting a dashboard using size, objects, views, filters, and legends
    • Best practices for making creative as well as interactive dashboards using the actions
    • Creating stories, including the intro of story points
    • Creating as well as updating the story points
    • Adding catchy visuals in stories
    • Adding annotations with descriptions; dashboards and stories
    • What is a dashboard?
    • Highlight actions, URL actions, and filter actions
    • Selecting and clearing values
    • Best practices to create dashboards
    • Dashboard examples; using Tableau workspace and Tableau interface
    • Learning about Tableau joins
    • Types of joins
    • Tableau field types
    • Saving as well as publishing data source
    • Live vs extract connection
    • Various file types
    • Quiz Module 11
  • icons-carri22 Module 12: Tableau Prep

    In this module the candidate will learn about Tableau prep, how Tableau prep helps combine join, sharp, and clean data for analysis, creation of smart examples with Tableau prep, and how data preparation is made simple and accessible, integrating Tableau prep with Tableau analytical workflow and a clear understanding the seamless process from data preparation to analysis with Tableau prep.
    • Introduction to Tableau Prep
    • How Tableau Prep helps quickly combine join, shape, and clean data for analysis
    • Creation of smart examples with Tableau Prep
    • Getting deeper insights into the data with great visual experience
    • Making data preparation simpler and accessible
    • Integrating Tableau Prep with Tableau analytical workflow
    • Understanding the seamless process from data preparation to analysis with Tableau Prep
    • Quiz Module 12
  • icons-carri22 Module 13: Integration of Tableau with R and Hadoop

    In this module the candidate will learn about Tableau with R and Hadoop, which includes Application and use cases of R, Deploying R on the Tableau platform, R functions in Tableau and The integration of Tableau with Hadoop. The candidate will also be provided with Hands-on Exercises which will enhance the knowledge of the topics learned and its working
    • Introduction to R language
    • Applications and use cases of R
    • Deploying R on the Tableau platform
    • Learning R functions in Tableau
    • The integration of Tableau with Hadoop
    • Quiz Module 13
  • icons-carri22 Module 14: Complimentary Module 1: Soft Skills Development

    • Business Communication
    • Preparation for the Interview
    • Presentation Skills
  • icons-carri22 Module 15: Complimentary Module 2: Resume Writing

    • Resume Writing

Know the complete offerings of our Data Science 360 Degree Course

Key Highlights

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96 Hours of Instructor-Led Sessions
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16 Hours of Live Master Sessions by Industry Experts
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192 hours of hands-on with Cloud Labs
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Job-Ready Portfolio of 10 Capstone Projects
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20 Industry Case Studies
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10+ Assignments and Mini Projects
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Get 1-Year Gold Membership of Henry Harvin® Data Science & Analytics Academy.
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Get 3 in 1 Placement support through Placement Drives, Premium access to the Job
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portal & Personalized Job Consulting.
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Earn a certificate of course from Henry Harvin
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32 Hours of Live Interactive Doubt Solving Sessions
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192 Hours of Self Paced Learning
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49 Auto-Graded Assessments
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103 Guided Hands-On Exercises
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2 Mock Interviews and 2 Hackathons
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Get 1-Year Gold Membership of Henry Harvin® Data Science & Analytics Academy.
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Get 3 in 1 Placement support through Placement Drives, Premium access to the Job
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portal & Personalized Job Consulting.
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Get 1-Year Gold Membership of Henry Harvin® Data Science & Analytics Academy.
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Get a guaranteed Internship with Henry Harvin® and in top MNCs like J.P. Morgan, Accenture & many more via Forage & 100Xsuite
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7 Hours of Mentorship by Industry Experts

About the Data Science 360 Degree Course

Overview

The Data Science 360 Degree Course stands out as a transformative educational experience, blending theory with real-world application. With a focus on project-based learning, participants solve problems unique to their sector and improve their problem-solving abilities. Led by seasoned professionals, the curriculum is enriched by the latest trends and tools, ensuring relevance in the evolving field.

Who Should Enroll?

  • Beginners
  • Students
  • Business Professionals
  • Tech Enthusiasts
  • Data Analysts

Trainers at Henry Harvin®

  • Meticulously chosen by our training partners and honored for their contributions by many organizations over the years.
  • Engaged in more than 100 keynote addresses for the Data Science 360 Degree Course.
  • Established leaders in the business world with over 13 years of experience.

Perks of Gold Membership

  • Unlock a 1 year Gold Membership: Access an extensive library of record videos, case studies, and projects related to the course.
  • Join a thriving Alumni Community: Connect with 460,000+ successful graduates.
  • Free Masterclass: Access to an exclusive masterclass for an entire year.
  • Gain Internship Experience: Attain practical experience with an internship with Henry Harvin®️.
  • Access Weekly Job Openings: 10+ job openings each week, designed to help you benefit in your career.
  • Engage in Real Business Initiatives: Gain experience through business initiatives during the program.

Recognitions of Henry Harvin®️ Education

  • Award-Winning Excellence: Honored with the 40 under 40 Business World Awards, Game-Based Learning Company of the Year, and Top Corporate Training Awards.
  • Stellar Reviews: With over 1,100 testimonials on YouTube averaging a 4.5-star rating, and more than 3,425 reviews across Google, Trustpilot, GoOverseas, and GoAbroad, our reputation speaks for itself.
  • Valued Partnerships: Become a part of a respected network endorsed by esteemed organizations such as the American Association of EFL, UKAF, UKK Cert, MSME, ISO 29990;2010, and the Project Management Institute (PMI).

Learning Benefits

  • Utilise the abilities and information you acquire from this comprehensive Data Science 360 Degree course to open doors to intriguing career prospects.
  • Manage difficult data problems and contribute significantly across a range of businesses.
  • Gain knowledge from seasoned business experts who can offer insightful advice.
  • Make connections with other students and industry professionals to grow your professional network.
  • Work on real-time data sets.
  • Gain recognition for your dedication to data science 360 Degree by earning a certification that can help you land a better job.
  • Benefit from a blended format that combines online and in-person classes.
  • Develop critical thinking and problem-solving skills by tackling real business challenges.
  • Enhance your resume by adding in-demand credentials and abilities that demonstrate your proficiency with data analysis and problem-solving.
  • Build a Startup in one of the most rewarding fields of today

Book a Live Class, For Free!

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By continuing you agree to Henry Harvin® Terms & conditions and Privacy Policy

Skills Covered

Filtering & Sorting Data

Connecting to Data

Calculations & Expressions of Data

Building graphs

Data Visualization

Integrating Tableau and R Programming

Rule Analysis

K-Means Clustering

CART Analysis

Regression

Data Manipulation

Cluster Analysis

Certifications

Get Ahead with Henry Harvin® Data Science 360 Degree Course

What you'll Learn in this course

Analytics Tools and Technologies

Power BI Concepts

Machine Learning Techniques

Python Programming

Statistics and Data Modeling

Data Cleaning

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FAQs

  • Which position I can attain after completing this course?

    You can apply for various positions:

    • Data Scientist
    • Data Visualization Specialist
    • Business Intelligence Developer
    • Data Analyst
    • Business Analyst
    • Dashboard Developer
    • Data Engineer
    • Testing Professionals
    • Data Science Consultant
  • How much time will it take to become certified as a Data Scientist?

    The Data Science 360 Degree Course typically takes eight to twelve weeks to complete. You can obtain the Data Science 360 Degree Course within 8 to 12 weeks of applying to the Data Science 360 Degree Course if you organise your study time, are ready for a variety of projects and assignments, and take a well-guided Data Science 360 Degree Course.

  • Does the Data Science 360 Degree Course have international recognition?

    Indeed, the certificate obtained after finishing Henry Harvin®'s Data Science 360 Degree Course is accepted throughout the world. Your professional profile and employment chances in data analytics will be much improved by this certification, which attests to your mastery of this course.