IBM Data Science Professional Certificate Coursera Quiz Answers

About IBM Data Science Professional Certificate Course

Kickstart your career in data science & ML. Build data science skills, learn Python & SQL, analyze & visualize data, build machine learning models. No degree or prior experience is required.

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.

Enroll on Coursera

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:

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, dashboard, and interactive map

There are 10 Courses in this Professional Certificate

Find IBM Data Science Professional Certificate Coursera Quiz Answers Below

Course 1: What is Data Science?

Course 2: Tools for Data Science

Course 3: Data Science Methodology

Course 4: Python for Data Science, AI & Development

Course 5: Python Project for Data Science

Course 6: Databases and SQL for Data Science with Python

Course 7: Data Analysis with Python

Course 8: Data Visualization with Python

Course 9: Machine Learning with Python

Course 10: Applied Data Science Capstone

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