Introduction to Data Science, Numpy and Pandas, Data Wrangling, Data Cleaning and Preparation, Visualization
What you will learn
Understand the basics of data
Learn the Pandas library to analyze data frames
Utilize different methods of data acquisition and data cleaning
Explore the visualization tools for different kinds of input data formats
Apply supervised and unsupervised learning to learn the hidden patterns from the data and predict the output
Why take this course?
This course offers a comprehensive introduction to the fundamentals of data science, focusing on both foundational concepts and practical applications. Designed for beginners, it combines theoretical insights with hands-on techniques to empower participants to analyze and interpret data effectively.
Students will learn core concepts such as data wrangling, statistical analysis, data visualization, and machine learning. The course emphasizes practical approaches to problem-solving using industry-standard tools like Python, along with libraries such as Pandas and Scikit-learn.
Real-world case studies will enable participants to build portfolios while exploring diverse domains like business, healthcare, and social sciences. By the end of the course, students will have the confidence to approach data-driven challenges and apply data science techniques to generate actionable insights.
Learners can Understand the key concepts of data science and its role in decision-making. Perform data cleaning, transformation, and analysis using programming tools. Develop and interpret data visualizations to communicate findings effectively. Apart from that, learners can apply basic machine learning algorithms to solve practical problems, Work with datasets from various domains in real-world case studies.
Beginners curious about data science, Professionals looking to add data analysis skills to their toolkit and majorly Students and individuals aspiring to pursue a career in data science can have a great learning experience from this course.