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Data Science: Real-time Exercises

 H2kinfosys offering Data Science - Real-time Exercises

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[Image: User-blue] Total Learners

850 Learners

[Image: Courses Duration] Course Duration

20 Hours

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    Instructor-led face-to-face live training

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    Huge course syllabus on latest technologies

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    Real-time projects to gain hands-on experience

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    Cloud Test Lab to practice on software tools and projects

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    Lifetime access to recorded class videos

About Data Science: Real-time Exercises Course

  • This course gives you a complete overview of what it entails to be a Data Scientist. In this course you will learn about cleaning and preparing your data for analysis, performing basic visualization of your data, modelling your data, curve-fit your data and ultimately about presenting your findings to the audience. This course will prepare you for the real-world Data Science scenarios by giving you sufficient practical exercises and assignments. In addition, tools like SQL, SSIS, Tableau and Gretl are also covered.

  • • I.T. career aspirants who wish to kickstart their career in one of the hottest technologies in the market 

    • Architects, software administrators, developers, testers who want to build an effective data processing application or perform big data analysis

    • ETL developers who wish to add an additional technology in their skillset on data management

Data Science: Real-time Exercises Course Syllabus

  • • Introduction

    • Visualization

    • Introduction to Tableau

     • Tableau for Data Mining

    • Advanced Data Mining

    • Modelling

    • Stats Refresher

    • Simple Linear Regression

    • Multiple Linear Regression

    • Logistic Regression

    • Building a robust geo-demographic segmentation model

    • Assessing your model

     • Drawing insights from your model

    • Model maintenance

    • Data Preparation

    • BI tools

    • Data Wrangling before the load

    • Uploading data using SSIS

    • Handling errors during ETL

    • SQL programming

    • Data Wrangling after the load

    • Handling errors during ETL

    • Communication

    • Working with people

    • Presenting for Data Scientists

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Data Science: Real-time Exercises Ratings

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