IBM: Analyzing Data with Python
This course is part of Ciencia de datos con Python Professional Certificate.
This introductory course teaches comprehensive data analysis with Python. You'll progress from Python basics to exploring diverse datasets through hands-on labs and assignments. The curriculum covers essential skills including data preparation, statistical analysis, meaningful data visualization, and future trend prediction. The course utilizes powerful libraries like pandas for data manipulation, NumPy for multidimensional arrays, SciPy for mathematical routines, and scikit-learn for machine learning applications. Students who successfully complete this IBM course can earn a verified digital skills badge, providing detailed credential of their acquired knowledge and abilities. The course features open discussion forums for student interaction, though they are no longer monitored by IBM's team.
Instructors:
Spanish
Español
Powered by
What you'll learn
Learn to import datasets, clean and prepare data for analysis, and build data pipelines
Master using Pandas DataFrames, NumPy arrays, and SciPy libraries for working with various datasets
Gain skills in loading, manipulating, analyzing and visualizing datasets with pandas
Develop machine learning models and make predictions using the scikit-learn library
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
Closed caption
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
Module Description
This course provides a comprehensive introduction to data analysis using Python. Students will learn to work with various datasets using powerful libraries including pandas DataFrames, NumPy multidimensional arrays, and SciPy. The curriculum begins with importing and cleaning data for analysis, then progresses to performing statistical analyses and creating meaningful data visualizations. Students will also learn to predict future trends using machine learning algorithms from scikit-learn. The course is structured around practical applications, with hands-on labs and assignments that reinforce key concepts. By the end of the course, participants will have developed skills in data preparation, manipulation, analysis, visualization, and predictive modeling that can be applied across numerous industries and data science scenarios.
Instructor
Pioneering Data Scientist Bridging AI Research and Education
Dr. Joseph Santarcangelo, a Data Scientist at IBM, brings a unique blend of academic excellence and practical expertise to the field of data science and artificial intelligence. With a Ph.D. in Electrical Engineering, his groundbreaking research focused on the intersection of machine learning, signal processing, and computer vision to understand how video content influences human cognitive processes. At IBM, he has established himself as a prominent educator and course developer, creating comprehensive learning materials that have reached hundreds of thousands of students worldwide. His teaching portfolio encompasses a wide range of technical subjects, from foundational Python programming to advanced topics in artificial intelligence, machine learning, and computer vision. Santarcangelo's ability to translate complex technical concepts into accessible learning experiences has made him an influential figure in data science education, maintaining consistently high ratings from learners while continuing to push the boundaries of applied machine learning and artificial intelligence research.
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.