Microsoft Data Science Bootcamp for Freshers Course Overview

Microsoft Data Science Bootcamp for Freshers Course Overview

The Microsoft Data Science Bootcamp for Freshers is designed to equip beginners with essential skills in data science. This comprehensive course covers fundamental topics such as data exploration, statistical analysis, and machine learning techniques. Participants will learn to utilize Microsoft tools effectively, fostering their ability to analyze data and generate insights.

Key learning objectives include mastering data pre-processing, developing predictive models, and visualizing data effectively. Upon completion, freshers will be well-prepared to tackle real-world data challenges, enhancing their prospects in the tech industry. With a hands-on approach, this bootcamp ensures that students can apply what they've learned directly to subsequent projects. Join us to kickstart your career in data science!

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3,375

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Course Fee 3,375
Total Fees
3,375 (USD)
  • Live Training (Duration : 90 Hours)
  • Per Participant
  • Includes Official Coursebook
  • Guaranteed-to-Run (GTR)
  • Classroom Training fee on request
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  • Live Training (Duration : 90 Hours)
  • Per Participant
  • Classroom Training fee on request
  • Includes Official Coursebook

♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

Prerequisites for the Microsoft Data Science Bootcamp for Freshers:


To ensure a productive learning experience in the Microsoft Data Science Bootcamp for Freshers, candidates should possess the following minimum knowledge and skills:


  • Basic understanding of mathematics and statistics, including concepts such as mean, median, standard deviation, and probability.
  • Familiarity with programming concepts, preferably in Python or R. No prior experience required, as we will cover foundational programming skills.
  • Basic knowledge of data analysis and visualization concepts is beneficial, but not mandatory.
  • Willingness to learn and explore new concepts in data science and analytics.
  • Motivated attitude and commitment to completing the bootcamp training.

This course is designed for beginners, so even if you have limited knowledge in some areas, you will be guided through the essential topics to build a strong foundation in data science.


Exam-Format Table
Exam ComponentDetails
Exam NameDP-100: Designing and Implementing a Data Science Solution on Azure
Exam TypeMultiple Choice Questions (MCQs)
Total Questions40-60
Passing Score700 (out of 1000)
Exam Duration180 minutes
LanguageEnglish
Exam ProviderMicrosoft
Exam RegistrationThrough Microsoft's official certification website or authorized testing centers
Certification Validity1 year (can be renewed)
Recommended TrainingDesigning and Implementing a Data Science Solution on Azure Training Course

Target Audience for Microsoft Data Science Bootcamp for Freshers

Microsoft Data Science Bootcamp for Freshers equips beginners with essential data science skills, providing a strong foundation for careers in data analysis, machine learning, and statistical modeling.


  • Recent college graduates in STEM fields
  • Aspiring data analysts
  • Entry-level data scientists
  • Business analysts looking to upskill
  • IT professionals transitioning to data science
  • Grad students pursuing a career in data
  • Professionals seeking to shift into analytics roles
  • Individuals interested in data visualization
  • Anyone with a passion for data-driven decision-making


Learning Objectives - What you will Learn in this Microsoft Data Science Bootcamp for Freshers?

Introduction:
The Microsoft Data Science Bootcamp for Freshers equips students with essential data science skills, focusing on practical tools and methodologies to analyze, interpret, and visualize data effectively.

Learning Objectives and Outcomes:

  • Understand fundamental data science concepts and methodologies.
  • Gain proficiency in using Microsoft tools for data analysis.
  • Learn to clean and preprocess data for analysis.
  • Apply statistical methods to derive insights from data.
  • Develop skills in data visualization techniques.
  • Master machine learning fundamentals and model deployment.
  • Learn to work with databases and SQL for data retrieval.
  • Understand the importance of data ethics and governance.
  • Build real-world projects to showcase data science skills.
  • Prepare for industry-relevant data science challenges.

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