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Menternships: Data Analytics Program

Blended theory and practice, holistic learning experience, and successful professional paths through expert mentorship, and hands-on internships.

Top-Rated 1,342+ Learners

Created By Sahil Garg,+1

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This Course includes:

  • Guidance from Experienced Mentors
  • Practical Hands-On Experience
  • Networking Opportunities
  • Customized Learning Paths
  • Career Development Support

Book a 1:1 Session

 

    Starts at

    This Course is Not Available in your region

    This Course includes:

    • Guidance from Experienced Mentors
    • Practical Hands-On Experience
    • Networking Opportunities
    • Customized Learning Paths
    • Career Development Support

    Book a 1:1 Session

     

    What You Will Learn

    • Opportunity to work on industry projects from top companies in India
    • Solve real-world challenges with a direct workplace context
    • 100% online, offering flexibility to work anytime, anywhere
    • Mentorship from current industry experts in leading corporates
    • Certifications from multiple companies based on project completion
    Show More

    Qualifications for Menternship

    • Enrollment in the Data Analytics course at upGrad KnowledgeHut is a prerequisite.
    • The eligibility criteria for each course are detailed within the respective course curriculum outlines.

    Curriculum

    1.

    Learning Objective:

    What are health insurance premiums made of? Let’s find out!

    Technologies used:
    • Data Visualization
    • Data Wrangling
    • Data Cleaning
    • SQL Programming

    Eligibility criteria: 

    • Should have completed till End of Microsoft PowerBI Training

    Please click here to fetch more information on the above-mentioned Menternship.


    2.

    Learning Objective:

    Should I invest? Should I not? Use business analytics to help investors make this crucial decision!

    Technologies used:
    • Data Visualization
    • Data Wrangling
    • Data Cleaning
    • SQL Programming

    Eligibility criteria: 

    • Should have completed till End of Microsoft PowerBI Training

    Please click here to fetch more information on the above-mentioned Menternship.


    3.

    Learning Objective:

    EDA practice - if you are eyeing a career in data science, this is the first step of your thousand-mile journey. Master Exploratory Data Analysis.

    Technologies used:
    • Data Analysis
    • Data Preparation
    • Hypothesis Testing

    Eligibility criteria: 

    • Should have completed till End of Data Visualization with Tableau

    Please click here to fetch more information on the above-mentioned Menternship.


    4.

    Learning Objective:

    How do big NGOs like Teach for India manage their 55k+ volunteers' data?

    Technologies used:
    • Data Analysis
    • Data Preparation
    • Hypothesis Testing

    Eligibility criteria: 

    • Should have completed till End of Data Analysis using Excel

    Please click here to fetch more information on the above-mentioned Menternship.


    5.

    Learning Objective:

    Business analysts in small businesses spend a lot of time making the most of Excel. Here is a fun challenge for you - create a motorcycle catalogue. 

    Technologies used:
    • Dashboard Designing
    • Data Analysis
    • Data Preparation
    • Hypothesis Testing

    Eligibility criteria: 

    • Should have completed till End of Data Analysis using Excel

    Please click here to fetch more information on the above-mentioned Menternship.


    6.

    Learning Objective:

    Can an Excel dashboard help you excel at your fitness goals? It can, actually. Start with menternship for practicing MS Excel and exploring the world of fitness coaching.

    Technologies used:
    • Dashboard Designing
    • Data Analysis
    • Data Preparation
    • Hypothesis Testing

    Eligibility criteria: 

    • Should have completed till End of Data Analysis using Excel

    Please click here to fetch more information on the above-mentioned Menternship.


    7.

    Learning Objective:

    How do companies track their marketing performance? 


    Technologies used:
    • Dashboard Designing
    • Data Analysis
    • Data Preparation
    • Hypothesis Testing

    Eligibility criteria: 

    • Should have completed till End of Microsoft PowerBI Training

    Please click here to fetch more information on the above-mentioned Menternship.


    8.

    Learning Objective:

    Is every day a good day to invest in gold? No! Help investors figure out the best time to buy gold.

    Technologies used:
    • Data Visualization
    • Data Wrangling
    • Data Cleaning
    • SQL Programming

    Eligibility criteria: 

    • Should have completed till End of Microsoft PowerBI Training

    Please click here to fetch more information on the above-mentioned Menternship.


    9.

    Learning Objective:

    What does it take to don the Orange Cap?

    Technologies used:
    • Analytical Skills
    • Insight Generation

    Eligibility criteria: 

    • Should have completed till End of Advanced Data Analysis

    Please click here to fetch more information on the above-mentioned Menternship.


    10.

    Learning Objective:

    Banks do not want to lose money! How can they reduce loan defaults?

    Technologies used:
    • Data Visualization
    • Data Wrangling
    • Data Cleaning
    • SQL Programming

    Eligibility criteria: 

    • Should have completed till End of Microsoft PowerBI Training

    Please click here to fetch more information on the above-mentioned Menternship.


    11.

    Learning Objective:

    We hope you like cricket. More than that, we hope you like playing with data!

    Technologies used:
    • Analytical Skills
    • Insight Generation

    Eligibility criteria: 

    • Should have completed till End of Advanced Data Analysis

    Please click here to fetch more information on the above-mentioned Menternship.


    12.

    Learning Objective:

    What does it take to get a credit card approved? Let's find out!

    Technologies used:
    • Data Visualization
    • Data Wrangling
    • Data Cleaning
    • Research and Intuition - FinTech
    • SQL Programming

    Eligibility criteria: 

    • Should have completed till End of Advanced Data Analysis

    Please click here to fetch more information on the above-mentioned Menternship.


    13.

    Learning Objective:

    What can the likes of ICICI and HDFC banks do to keep their customers happy?

    Technologies used:
    • Data Visualization
    • Data Wrangling
    • Data Cleaning
    • Research and Intuition - FinTech
    • SQL Programming

    Eligibility criteria: 

    • Should have completed till End of Advanced Data Analysis

    Please click here to fetch more information on the above-mentioned Menternship.


    14.

    Learning Objective:

    How do Spotify, YouTube, and Netflix recommend just the right 'play next'? All you need to figure this out is an internet connection and MS Excel.

    Technologies used:
    • Data Analysis
    • Data Preparation
    • Hypothesis Testing

    Eligibility criteria: 

    • Should have completed till End of Data Visualization with Tableau

    Please click here to fetch more information on the above-mentioned Menternship.


    15.

    Learning Objective:

    India is home to 100 unicorns! Not the one-horned magical creatures, but 1 billion-worth companies. Where do unicorns come from? Let's find out with some data analysis. You need a Power BI account for this menternship.

    Technologies used:
    • Dashboard Designing
    • Data Analysis
    • Data Preparation
    • Hypothesis Testing

    Eligibility criteria: 

    • Should have completed till End of Microsoft PowerBI Training

    Please click here to fetch more information on the above-mentioned Menternship.


    16.

    Learning Objective:

    Mine the data from any Play Store and find out what the hottest, most profitable app categories are. You will need to use Python (Data Science) for this menternship.

    Technologies used:
    • Data Analysis
    • Data Preparation
    • Hypothesis Testing

    Eligibility criteria: 

    • Should have completed till the end of Advanced Data Analysis

    Please click here to fetch more information on the above-mentioned Menternship.


    17.

    Learning Objective:

    A simple and brilliant opportunity to build proof of work in the extremely in-demand data science field of insurtech.

    Technologies used:
    • Data Analysis
    • Data Preparation
    • Hypothesis Testing

    Eligibility criteria: 

    • Should have completed till the end of Microsoft PowerBI Training

    Please click here to fetch more information on the above-mentioned Menternship.


    18.

    Learning Objective:

    Football is more than a sport; it's a religion. Analyze the career of one of the torchbearers of the epic sport!

    Technologies used:
    • Analytical Skills
    • Insight Generation

    Eligibility criteria: 

    • Should have completed till the end of Microsoft PowerBI Training

    Please click here to fetch more information on the above-mentioned Menternship.


    What Learners Are Saying

    I feel this internship is a great step for me to learn, practice and exhibit the skills. Truly this menternship helped me through the way.

    V
    Vaishnavi Kupate

    It has been a wonderful experience working on this project. It has given me confidence that I can perform well in the real industry.

    P
    Preeti

    Course Advisors

    Sahil Garg
    Sahil Garg

    Partnerships Manager

    Sahil at MentorMind works to ensure that partners and learners have an enriching experience. He has multifaceted experience in managing learning programmes for young professionals. 

    Aman Singh Verma
    Aman Singh Verma

    Senior Data Scientist

    Aman is a seasoned data scientist with over four years of extensive industry experience. Driven by a profound passion for leveraging data-driven insights and solutions, he excels in tackling intricate real-world challenges. Aman's talent extends to mentoring, where he exhibits a remarkable ability to guide and inspire the next generation of learners.

    Course Advisors

    Sahil at MentorMind works to ensure that partners and learners have an enriching experience. He has multifaceted experience in managing learning programmes for young professionals. 

    Sahil Garg
    Sahil Garg

    Partnerships Manager

    Aman is a seasoned data scientist with over four years of extensive industry experience. Driven by a profound passion for leveraging data-driven insights and solutions, he excels in tackling intricate real-world challenges. Aman's talent extends to mentoring, where he exhibits a remarkable ability to guide and inspire the next generation of learners.

    Aman Singh Verma
    Aman Singh Verma

    Senior Data Scientist

    Frequently Asked Questions

    Yes, you will experience upGrad KnowledgeHut's immersive learning in an on-demand format. This will include e-learning material to help you:

    • LEARN with recall quizzes, interactive ebooks, and case studies
    • ASSESS your skills progression with diagnostic, module-level, and final assessments
    • PRACTICE with real-world simulations and Cloud Labs
    • GAIN INSIGHTS with real-time reports and analytics on how you're progressing, your learning challenges, and suggestions of sections to revisit to build competency in the required areas.

    Yes, our online course is designed to give you flexibility to skill up as per your convenience. The course is delivered in a Self-Paced mode so that you can balance your work and learning as per your schedule.

    Yes! Upon passing this online course, you will receive a signed certificate of completion from upGrad KnowledgeHut. Thousands of upGrad KnowledgeHut alumni use their course certificate to demonstrate skills to employers and their networks.

    More than the certificate, however, you will get to showcase your newly acquired skills by working on real-world projects and adding them to your portfolio. upGrad KnowledgeHut’s online courses are well-regarded by industry experts, who contribute to our curriculum and use our tech programs to train their own teams.

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