Udemy – Hands-on Data Science Skills(Python Machine Learning,Pandas) 2024-6

To equip you with the necessary tools for effective data analysis, this course covers essential programming languages ​​such as Python. Whether you’re manipulating data with Pandas, performing numerical operations with NumPy, or creating insightful visualizations with Matplotlib and Seaborn, you’ll develop a diverse skill set that forms the backbone of data mining projects. The main focus of the course is on practical learning. You will gain hands-on experience in collecting, cleaning and analyzing data from a variety of sources. You’ll improve your ability to turn raw data into actionable insights that drive business decisions. During the course, you will apply your new knowledge to practical projects that simulate real-world challenges. Whether it’s forecasting house prices using regression models or building a web application for interactive data analysis, these projects provide a platform to showcase your skills and build a professional portfolio.

What you will learn in Hands-on Data Science Skills (Python Machine Learning Pandas) course

• Understanding the fundamental concepts of data mining
• Installing Python and setting up the development environment on Windows and macOS
• Understanding the concept of virtual environments and creating/managing them
• Understanding the applications and impact of data mining industry
• Distinguish between structured and unstructured data
• Getting to know Jupyter Notebook and using it for interactive data analysis
• Explore and manipulate data using Pandas DataFrames
• Create and manipulate Pandas Series for efficient data management
• Load the dataset into Pandas and perform initial data inspection and cleaning
• Data transformation and analysis using Pandas methods
• Data visualization using Matplotlib and Seaborn for insights and reporting
• Understand supervised, unsupervised and reinforcement learning techniques
• Data preprocessing for machine learning models, including handling of missing values ​​and coding of categorical variables
• Building, training and evaluating machine learning models using scikit-learn
• Measure model performance using metrics such as accuracy, confusion matrix, and classification report
• Machine learning model deployment for real-time predictions and understanding model interpretation techniques

This course is suitable for people who

• Up-and-coming Data Scientists: People looking to enter the field and build a strong foundation in data analytics and machine learning.
• Students and Graduates: University students or recent graduates looking to complement their academic knowledge with practical real-world skills in data analysis and machine learning.
• Professionals changing career paths: Individuals from diverse professional backgrounds (eg IT, finance, healthcare) interested in transitioning into data-driven roles.
• Data Analysts and Engineers: Professionals currently working in related fields who want to expand their skill sets and deepen their understanding of data manipulation, visualization, and predictive modeling.
• Entrepreneurs and business owners: People looking to use data mining to drive business decisions, optimize processes, and gain competitive advantage in their industries.
• Anyone interested in data mining: Enthusiasts with a curiosity for data-driven insights and a desire to understand how data mining is shaping many aspects of modern life.

Installation guide

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