The IBM Data Science Professional Certificate is a comprehensive program offered by Coursera in collaboration with IBM. This certificate program is designed to equip individuals with the skills and knowledge needed to pursue a career in data science. Through a series of hands-on projects and interactive lessons, participants learn essential concepts, techniques, and tools used in data science.

• Industry-Relevant Curriculum: The course curriculum is designed in collaboration with industry experts from IBM, ensuring that participants learn the most up-to-date and relevant skills in data science.
• Hands-On Projects: Participants have the opportunity to work on real-world projects, allowing them to apply theoretical concepts to practical scenarios and build a strong portfolio.
• Flexible Learning: The course is available online through Coursera, providing flexibility for participants to learn at their own pace and schedule.
• IBM Credential: Upon completion of the program, participants receive the IBM Data Science Professional Certificate, which is recognized by employers globally and can enhance career prospects.

1. What is Data Science?

   • Introduction to the field of data science
   • Understanding the role and importance of data scientists
   • Exploring various applications and domains of data science

2. Tools for Data Science

   • Proficiency in using essential tools for data science, such as Jupyter Notebooks, GitHub, and Watson Studio
   • Understanding version control with Git and GitHub
   • Familiarity with IBM Cloud services for data science projects

3. Data Science Methodology

   • Learning the data science methodology for tackling data science projects
   • Understanding the lifecycle of a data science project, including problem definition, data preparation, modeling, evaluation, and deployment

4. Python for Data Science, AI & Development

   • Mastery of Python programming language for data science and AI applications
   • Understanding data structures, control flow, functions, and object-oriented programming in Python
   • Proficiency in using libraries such as NumPy, Pandas, and scikit-learn for data manipulation and machine learning

5. Python Project for Data Science

   • Application of Python programming skills to real-world data science projects
   • Experience in solving data science problems using Python libraries and tools
   • Developing critical thinking and problem-solving skills through project-based learning

6. Databases and SQL for Data Science with Python

   • Proficiency in working with databases and SQL for data analysis
   • Understanding database management systems (DBMS) and relational database concepts
   • Learning SQL queries for data manipulation, querying, and management

7. Data Analysis with Python

   • Advanced data analysis techniques using Python
   • Exploratory data analysis (EDA) methods for understanding data distributions, correlations, and patterns
   • Statistical analysis and hypothesis testing using Python libraries such as SciPy and StatsModels

8. Data Visualization with Python

   • Mastery of data visualization techniques using Python libraries like Matplotlib, Seaborn, and Plotly
   • Creating informative and visually appealing plots, charts, and graphs to communicate insights from data effectively
   • Understanding principles of data visualization design and best practices

9. Machine Learning with Python

   • Understanding fundamental concepts of machine learning algorithms and techniques
   • Hands-on experience in building and evaluating machine learning models using Python
   • Knowledge of supervised and unsupervised learning methods, model evaluation, and hyperparameter tuning

10. Applied Data Science Capstone

    • Integration of knowledge and skills acquired throughout the program in a real-world data science project
    • Experience in problem formulation, data collection, data cleaning, exploratory data analysis, modeling, and presentation of results
    • Collaboration and teamwork in a capstone project environment

For more information and enrollment, visit the IBM Data Science Professional Certificate page on Coursera.