GraceMar-Online-Trainings-and-Certs - Flipbook - Page 7
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IBM Data Science Professional Certificate
Kickstart your career in data science & ML. Build data science skills, learn
Python & SQL, analyze & visualize data, build machine learning models.
Set and maintain flexible deadlines. No degree or prior experience
needed to get started.
3 Months at suggested pace of 12 hours/week
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Build the Skills to Get Job Ready
Hands-On Projects
Earn a Career Credential
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.
WHAT YOU WILL LEARN
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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
Applied Learning Project
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:
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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