Data Science is an interdisciplinary field that uses scientific methods, algorithms, processes, and systems to extract insights and knowledge from structured and unstructured data. It combines expertise in statistics, computer science, and domain knowledge to analyse complex datasets and turn them into actionable insights for decision-making. Data scientists use techniques like machine learning, predictive modelling, statistical analysis, and data visualization to uncover patterns, trends, and correlations within data.
Data Science is an interdisciplinary field that uses scientific methods, algorithms, processes, and systems to extract insights and knowledge from structured and unstructured data. It combines expertise in statistics, computer science, and domain knowledge to analyse complex datasets and turn them into actionable insights for decision-making. Data scientists use techniques like machine learning, predictive modelling, statistical analysis, and data visualization to uncover patterns, trends, and correlations within data. The field of data science includes working with large datasets (big data), applying tools like Python, R, SQL, and Hadoop, and utilizing advanced technologies such as artificial intelligence (AI) and deep learning. Data scientists play a key role in various industries, helping businesses optimize operations, forecast trends, enhance customer experiences, and innovate products and services. A career in data science often involves data collection, cleaning, exploration, model building, and communication of results to non-technical stakeholders. As businesses increasingly rely on data to drive decisions, the demand for skilled data scientists has grown significantly, making it one of the most sought-after professions today.
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Tech Stack: Python, Pandas, Matplotlib Description: Build a budget tracking app that allows users to input income and expenses and visualize their spending patterns over time. Use **Pandas** for data manipulation and **Matplotlib** for visualizations.
Tech Stack: Python, Pandas, Seaborn Description: Create a dashboard to analyze and visualize sales data, with charts to explore trends, averages, and sales distribution. This project will focus on data cleaning, aggregation, and visualization.
Tech Stack: Python, Scikit-learn, K-means Clustering Description: Use clustering algorithms like **K-means** to segment customers based on purchasing behavior. Visualize the segments and provide insights on targeted marketing strategies.
Tech Stack: SQL, Python (SQLAlchemy) Description: Build a tool that connects to a database and cleans data by removing duplicates, handling missing values, and applying necessary transformations. Implement advanced SQL queries for data cleaning.
Tech Stack: Python, TensorFlow/Keras Description: Build a convolutional neural network (CNN) to classify images from a dataset, such as identifying different types of animals or objects in pictures. This will include training a CNN model using TensorFlow or Keras.
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