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Maj-a/README.md
  • 👋 Hi, I'm Maja.

  • 👀 I’m passionate about People Analytics & People Science.

  • 🌱 Currently, I’m learning Unsupervised Multivariate Methods (exam date is fast approaching!).

  • 💞️ I’m eager to collaborate on data science and analytics projects, especially those related to HR.

  • 📫 Let's connect on LinkedIn

  • ⚡ Fun fact: I can do a headstand 🧘‍♀️😉

  • ℹ️ About Me: I am a Data Science student with a background in business and HR. My goal is to integrate analytics and data science with business, with a particular focus on the people side. I believe understanding your workforce is as crucial as understanding your customers. Nothing drives business performance better than a culture of engaged employees.

  • 💡 Thought Leaders I Follow and Their Views on People Analytics:

    • 💭 Keith McNulty: “Organizations that leverage people analytics and foster high levels of employee engagement see a direct correlation with superior business results. Engagement drives productivity, and productivity drives performance.”

    • 💭 David Ulrich: “The key to effective HR is to focus on the impact you have on the business. By using people analytics to measure and manage employee performance and engagement, HR can drive significant business outcomes.”

    • 💭 Josh Bersin: “People analytics has moved from being a ‘nice to have’ to a critical tool for understanding and managing talent. Companies that use people analytics are more likely to make better decisions, improve employee engagement, and drive business performance.”

    • 💭 Brett Minchington: “The ability to attract, engage, and retain top talent is the single most important competitive advantage in today’s economy. People analytics provides the insights needed to enhance employee engagement and drive organizational success.”

  • 📚 To Check Out Some of My Recent Work and Ongoing Projects Scroll Down ⤵️ I am continuously updating this with new projects and insights. Upcoming projects include work on multilinear regression, logistic regression, and time series analysis, among others.

    • Repository is like a folder with files, where project's files, including code, documentation, and other resources, are stored. So feel free to clik and check any of the below ⤵️ and let me know if you have any questions or comments.

--->

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  1. Data-Visualisation Data-Visualisation Public

    Data Visualization is another element of data exploration. After concluding descriptive statistics, creating visualizations like histograms, scatter plots, and box plots helps to understand distrib…

    Python

  2. Descriptive-Statistics- Descriptive-Statistics- Public

    During this part, we explore the data. We calculate basic statistics (mean, median, mode, variance) and we check for an outliers. All to understand more and to summarize the dataset.

    R

  3. EDA_Data-management. EDA_Data-management. Public

    Exploratory Data Analysis -> Data Management -> Data Inspection This stage involves reviewing the data within your environment. I call it a “getting to know the data” phase, where you examine the n…

    R

  4. Maj-a Maj-a Public

    Config files for my GitHub profile.

  5. PowerBI_HR-Dashboards PowerBI_HR-Dashboards Public

  6. Programming---first-steps. Programming---first-steps. Public

    Here I share my first steps in R and Python programming.

    Python