10 Data Analysis Projects to land your first Job.
<p>To land a Job in a very technical field such as Data analysis you need to have a solid portfolio, This portfolio will be your identity Card that you will introduce yourself to the world through it.</p>
<p>So Here are 10 entry-level projects you can test your limits & skills through these Ideas, where I will also mention the difficulty of the project & The data Source which you can download to start with it right away</p>
<p>Important note: if you are still wondering what to study & where to go in this field, I will publish another article series to guide you to follow step by step that will help you master the essential skills, but for now the main focus is the portfolio creating step.</p>
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<li>EDA for the Iris Flower dataset:</li>
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<p>DIFFICULTY: EASY</p>
<p>Data source: The Iris Flower Dataset — <a href="https://archive.ics.uci.edu/ml/datasets/iris" rel="noopener ugc nofollow" target="_blank">https://archive.ics.uci.edu/ml/datasets/iris</a></p>
<p>Tools: Python (Pandas, Matplotlib, Seaborn)</p>
<p>To start with this data, you can import the dataset into a Jupyter Notebook using Pandas. Then, you can perform exploratory data analysis using Matplotlib and Seaborn to create visualizations such as scatterplots, histograms, and boxplots.</p>
<p>2. Sales Analysis:</p>
<p>DIFFICULTY: MEDIUM</p>
<p>Data source: Superstore Sales Dataset — <a href="https://www.kaggle.com/jr2ngb/superstore-data" rel="noopener ugc nofollow" target="_blank">https://www.kaggle.com/jr2ngb/superstore-data</a></p>
<p>Tools: SQL (MySQL), Tableau</p>
<p>To start with this data, you can import the dataset into a MySQL database and use SQL queries to perform data analysis. You can then connect Tableau to the database to create visualizations such as bar charts, line charts, and heat maps.</p>
<p>3. Customer Segmentation:</p>
<p>DIFFICULTY: Advanced</p>
<p>Data source: Online Retail Dataset — <a href="https://www.kaggle.com/vijayuv/onlineretail" rel="noopener ugc nofollow" target="_blank">https://www.kaggle.com/vijayuv/onlineretail</a></p>
<p>Tools: Python (Pandas, Scikit-Learn), Tableau</p>
<p>To start with this data, you can import the dataset into a Jupyter Notebook using Pandas. Then, you can use Scikit-Learn to perform clustering algorithms such as K-Means to segment the customers. You can then connect Tableau to the data to create visualizations such as scatterplots and heat maps.</p>
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