Learn the fundamentals of data science
Data science is the study of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions. It is a rapidly growing field given the vast volumes of data with plenty of untapped potential.
Starting a journey as a beginner can be both exciting and challenging. Before diving deep in the field these are some of the key concepts you should understand before learning what data science is.
1.Programming: Learn a programming language like Python, which is widely used in data science. There are many resources available online and in libraries to learn Python
2.Statistics: Statistics is essential for understanding and analyzing data. You should learn about probability, descriptive statistics, and inferential statistics.
3.Database: Understand how databases work, how to manage them, and how to extract data from them.
4.Machine Learning: Machine learning is a subfield of computer science that gives computers the ability to learn without being explicitly programmed. Machine learning is used in many data science applications, such as image recognition, natural language processing, and fraud detection.
Gain experience with data science tools
1.Python libraries: NumPy, Pandas, Matplotlib, Seaborn, and Scikit-learn are some of the most popular Python libraries for data science. These libraries provide a variety of functions for data manipulation, visualization, and machine learning.
2.SQL databases: SQL is a language used to query and manage relational databases. MySQL, PostgreSQL, and Oracle are some of the most popular SQL databases.
3.Cloud computing platforms: Cloud computing platforms like AWS, Azure, and Google Cloud Platform offer a variety of services for data science, such as data storage, data processing, and machine learning.
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