Coursera offers a series of Data Science courses and specialization programs, and one of the popular ones is the “IBM Data Science Professional Certificate.” This specialization is created in partnership with IBM and provides learners with a comprehensive foundation in data science, including hands-on experience with various data science tools and techniques. Here are some key details about the Coursera IBM Data Science Professional Certificate:

Overview:

• Provider: Coursera in partnership with IBM
• Duration: It typically takes around 9 to 12 months to complete all the courses, but learners can choose their pace.
• Prerequisites: While there are no strict prerequisites, a basic understanding of Python programming and some mathematical concepts can be beneficial.

Course Content: The IBM Data Science Professional Certificate consists of multiple courses that cover a wide range of topics in data science, including:

1. What is Data Science?

   • Introduction to data science concepts and the data science process.

2. Tools for Data Science

   • Practical training on using data science tools, including Jupyter notebooks, GitHub, and IBM Watson Studio.

3. Data Science Methodology

   • Learning about the key steps in the data science methodology, including business understanding, data preparation, data modeling, evaluation, and deployment.

4. Python for Data Science and AI

   • An introduction to Python programming for data science, including libraries like pandas, numpy, and scikit-learn.

5. Databases and SQL for Data Science

   • Exploring databases, data retrieval, and using SQL for data analysis.

6. Data Visualization with Python

   • Creating data visualizations using Python libraries like Matplotlib and Seaborn.

7. Machine Learning with Python

   • Covering machine learning algorithms, model evaluation, and deployment.

8. Applied Data Science Capstone

   • A final project where learners apply their knowledge to solve a real-world data science problem.

Hands-On Labs and Projects: Throughout the specialization, learners engage in hands-on labs and complete real-world projects that help reinforce their understanding of data science concepts and tools.

Certification: Upon successfully completing all the courses and the final capstone project, learners receive the IBM Data Science Professional Certificate, which can be a valuable credential when seeking data science-related positions.