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Data Science 101
Course
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.
Flexible Schedule
Beginner Level
Mentor Support
Estimated Time
4 weeks, online
2-4 hours/week
2-4 hours/week
Through the power of data science, businesses are gleaning valuable insights that give them a competitive edge. By manipulating large pools of information, data scientists are able to present stakeholders with critical analysis that enables them to make informed decisions about their products, market place, and internal operations. Individuals with strong skills in data science are having a significant impact on the performance of businesses, therefore, and enjoying an interesting and rewarding career.
In this course, you will learn about the basics of data science and discover how organizations are using data science. You will explore what data scientists do and you will look at the use cases and applications of data science. Plus, you will learn how to start a career in this exciting field.
For individuals keen to take their first step in the world of data science, this Data Science 101 course will teach you the key concepts you need to move forward. Plus, it will provide you with the necessary foundation you need to progress through other courses to further build your skills.
This course comprises five purposely designed modules that take you on a carefully defined learning journey.
It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 2-4 hours per week, you will complete the course in 4 weeks. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And don't worry, you're not alone! You will be encouraged to stay connected with your learning community and mentors through the course discussion space.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include discussion space, videos, reading material, quizzes, exercise and final assignment.
Once you have successfully completed the course, you will earn your IBM Certificate.
As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. 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 may vary package wise.
You will:
- Have a good understanding of the definitions of data science.
- Have a grasp of data science in a business context.
- Understand the use cases for data science.
- Individuals looking for a good introduction to data science.
- Individuals who would like to explore the tools and technologies used in data science.
- Invididuals who would like to begin understanding how to apply a particular data science approach to their work.
No prerequisites are required for taking this course
Course Outline
General Information
Learning Objectives
Syllabus
Grading Scheme
Change Log
Copyrights and Trademarks
Learning Objectives
What is data science? (2:37)
There are many paths to data science (3:55)
Advice for aspiring data scientists (2:59)
What is the cloud? (3:16)
Readings
Graded Review Questions
Learning Objectives
A day in the life of a data science person (3:54)
R versus Python (1:52)
Data Science tools and technology (5:41)
Readings
Graded Review Questions
Learning Objectives
How should companies get started in Data Science? (3:01)
Recruiting for data science (7:41)
Readings
Graded Review Questions
Learning Objectives
Applications of data science (6:28)
Readings
Graded Review Questions
Learning Objectives
Things data science people say (1:05)
Readings
Graded Review Questions
Instructions
Final Exam
Certificate
Badges
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
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.
Type of 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
This course has been created by
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