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IBM projects

Primary LanguageJupyter Notebook

IBM Data Science Professional Certificate

There are 10 Courses in this Professional Certificate

  1. What is Data Science?
  2. Tools for Data Science
  3. Data Science Methodology
  4. Python for Data Science, AI & Development
  5. Python Project for Data Science
  6. Databases and SQL for Data Science with Python
  7. Data Analysis with Python
  8. Data Visualization with Python
  9. Machine Learning with Python
  10. Applied Data Science Capstone

Learn what data science is, the various activities of a data scientist’s job, and methodology to think and work like a data scientist

Develop hands-on skills using the tools, languages, and libraries used by professional data scientists

Import and clean data sets, analyze and visualize data, and build and evaluate machine learning models and pipelines using Python

Apply various data science skills, techniques, and tools to complete a project and publish a report

Skills

  • Data Science
  • Python Programming
  • Data Analysis
  • Pandas
  • Numpy
  • Ipython
  • Cloud Databases
  • Relational Database Management System (RDBMS)
  • SQL
  • Predictive Modelling
  • Data Visualization (DataViz)
  • Model Selection

Tools:

Jupyter / JupyterLab, GitHub, R Studio, and Watson Studio

Libraries:

Pandas, NumPy, Matplotlib, Seaborn, Folium, ipython-sql, Scikit-learn, ScipPy, etc.

Projects:

Random album generator, predict housing prices, best classifier model, Predicting successful rocket landing, dashboa rd and interactive map

Applied Learning Project

This Professional Certificate has a strong emphasis on applied learning. Except for the first course, all other courses include a series of hands-on labs in the IBM Cloud that will give you practical skills with applicability to real jobs, including:

https://www.coursera.org/professional-certificates/ibm-data-science#courses