
Data Science 101
Explore the fundamentals of data science. Hear from real practitioners what it means to work in data science, and prepare for a rewarding career.
Data Science 101 Highlights
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Duration
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Fee US$ 99 - US$ 199 |
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Duration
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Fee US$ 99 - US$ 199 |
Course Outline
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Once you have completed this course, you will earn your certificate.
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Course details
Certificate
- IBM Certificate
About this course
- 05 Modules
- 05 Skills
Includes
- Discussion space
- 05 Quizzes
- 11 Videos
- 01 Final exam
Exercises to explore
- R
- Python
- Cloud
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Shingai Manjengwa
- Director, Technical Education
- View on LinkedIn
FAQs
Data science is a blend of programming tools, statistical analysis, algorithms, and machine learning principles. It involves the use of multiple approaches including statistics, scientific methodologies, artificial intelligence (AI), and data analysis.
A data scientist will utilize all these instruments to then discover meaningful patterns hidden in raw data. They tap into a variety of skills to evaluate data acquired from the web, smartphones, customers, sensors, and other sources. And it is data science that provides the framework and methodologies to glean the valuable insights required. In working this way, the trends that data scientists identify then enable businesses to become more efficient through improved decision making and more innovative with respect to their products and services.
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.
The process of data gathering and analysis:
- Begin the process of discovery; ask the right questions.
- Assemble information.
- Cleanse and process the data.
- Compile and save data.
- Carry out data inquiry and analysis.
- Select the best tools, methodologies, models and algorithms to use.
- Use data science techniques such as machine learning, statistical modelling, and artificial intelligence to tackle problems as they arise.
- Evaluate and improve the results.
- Notify relevant parties of the outcome.
- Obtain feedback and adjust findings appropriately.
- Start the next project; follow the same steps.
The demand for data scientists is high and salaries are competitive, which is why the field has been dubbed "the most promising career" by LinkedIn and "the best job in America" by Glassdoor.
Yes, this Data Science 101 course is delivered entirely online. There is no set schedule for completing modules or submitting tasks, so there is no need to complete them on a specific day or time. You can, therefore, work at your own pace as long as the course is finished before the conclusion of your enrollment period.
Yes, Data Science 101 offers mentoring options. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Plus, depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services will vary across packages.
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