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.
In addition to earning a Professional Certificate from Coursera, you’ll also receive a digital badge from IBM recognizing your proficiency in data science.
The Program
- Что такое наука о данных?
- Tools for Data Science.
- Data Science Methodology.
- Python for Data Science, AI & Development.
- Python Project for Data Science.
- Databases and SQL for Data Science with Python.
- Анализ данных с Python.
- Data Visualization with Python.
- Машинное обучение с использованием Python.
- Applied Data Science Capstone.
What will you learn
- 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.