About This workshop and the materials in this repo are for anyone who is interested in working with Data Science to produce high quality, working style! Check out follow course link if you think it is interested.
Course Link: IBM Data Science Professional Certificate
The courses enlisted as follows:
- C1-What is Data Science?
- C2-Tools for Data Science
- C3-Data Science Methodology
- C4-Python for Data Science, AI & Development
- C5-Python Project for Data Science
- C6-Database and SQL for Data Science with Python
- C7-Data Analysis with Python
- C8-Data Visualization with Python
- C9-Machine Learning with Python
- C10-Apllied Data Science Capstone
Data science is one of the hottest professions of the decade, and the demand for data scientists who can analyze data and communicate results to inform data driven decisions has never been greater. This Professional Certificate from IBM will help anyone interested in pursuing a career in data science or machine learning develop career-relevant skills and experience. It’s a myth that to become a data scientist you need a Ph.D. Anyone with a passion for learning can take this Professional Certificate – no prior knowledge of computer science or programming languages required – and develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry level data scientist. The program consists of 9 online courses that will provide you with the latest job-ready tools and skills, including open source tools and libraries, Python, databases, SQL, data visualization, data analysis, statistical analysis, predictive modeling, and machine learning algorithms. You’ll learn data science through hands-on practice in the IBM Cloud using real data science tools and real-world data sets. Upon successfully completing these courses, you will have built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in data science.
Tools: Jupyter / JupyterLab, GitHub,
Libraries: Pandas, NumPy
Projects:
Total Hours: ~132 Hrs
