IBM Professional Certificate
Earn your professional certificate on completion
About this program
180 -240 Hours of content
100 Hands on labs - over 80 hours
Exercises to explore
- Web scraping
- IBM Cloud
- Jupyter notebook
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This program is offered through a series of 10 courses.
Your IBM Professional Certificate will be issued once you have completed the full program and your capstone project has been successfully evaluated by IBM.Enroll for this program
Earn your certificate
Once you have successfully completed this program, you will earn IBM Data Science Professional certificatePreview - Digital Certificate
Data science is a blend of programming tools, statistical analysis, algorithms, and machine learning principles. The goal of a data scientist is to utilize all of these instruments to discover meaningful patterns hidden in raw data. And it is data science that provides the framework and methodologies to achieve this.
Data scientists should have a good understanding of data analysis as well as strong programming skills. They need to develop skills in two distinct areas:
Technical Skills - To be a good data scientist, you must excel in mathematics and statistics. However, other technological expertise is also required, including programming, knowledge of analytical tools, and the ability to manage unstructured data.
Non-Technical Skills - An individual’s soft skills - sometimes referred to as people skills - are classified as non-technical. To be a good data scientist, you need exceptional business sense, strong communication skills, and data intuition.
Data scientists work collaboratively with business stakeholders to figure out how data can help them accomplish their goals. They create algorithms and prediction models to extract the required data for a given objective in order to then analyze the data, create meaningful, visual reports, and share information.
Within data science, there are many roles for data scientists to perform:
- • Data Scientist - A data scientist investigates data trends in order to assess their influence on a company.
- • Data Analyst - A data analyst analyzes data to determine market trends.
- • Data Engineer – A data engineer is in charge of creating, designing, and managing an organization’s database(s).
- • Business Intelligence Analyst - A business intelligence analyst assists in the analysis of data, with the aim of increasing the efficiency of the organization and generating more revenue.
- • Marketing Analyst - A marketing analyst researches and recommends which products should be produced for which target clients, and at what prices they should be offered.
Python is a popular language for those who work in data science. Many employers will advertise roles stating that applicants require coding skills in Python. We therefore recommend that you seek to develop skills in Python if you wish to become a data scientist.