Acquire critical skills for tackling data science problems effectively. Learn how to problem solve with data to address real-world challenges and business scenarios.
Build your knowledge of a crucial aspect of data science and develop your skills in this exciting field.
If you wish, you can enroll for the program also or enroll this course individually.
The data a business holds is a valuable resource. By applying proven methodologies, organizations can glean critical insights that give them a competitive edge. To achieve this however, their data scientists need to have a good grasp of the right questions to ask, as well as the necessary knowledge to analyze the data. Developing a strong ability to manage, decipher and analyze new and big data is therefore vital to working in data science.
During this course, you will be introduced to the major steps involved in tackling a data science problem. You will explore the key stages in data science methodology and build an appreciation of how to apply these to developing the right analytic approach. You will learn how to solve data science problems and come to understand the purpose of data modeling. And you will become familiar with the characteristics of the modeling process, what happens after model deployment, and the importance of model feedback.
By building your knowledge of data science methods, you will develop the skills required to ensure that data used is both relevant and properly manipulated to address business and real-world challenges. Plus, you will be another step closer to gaining IBM Data Science Professional Certification.
This course comprises six purposely designed modules that take you on a carefully defined learning journey. If you are thinking about taking the course separately, it is worth noting that it is part of the IBM Data Science Professional Certificate Program and you may want to consider enrolling for the whole program rather than just enrolling for one course at a time.
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 3-7 hours per week, you will complete the course in 7 weeks. However, as long as the course is completed before the end date, you can work at your own pace.
The materials for each module will become available when you start the particular module. Methods of learning and assessment will include videos, reading material, and online exams questions.
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 be able to:
No experience required
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.
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Designed by the industry for the industry so you can build job-ready skills.
Competency building and global certifications employers are actively looking for.
IBM Certificate
06 Modules
01 Skills
01 Final exam
06 Quizzes
13 Videos
Data collection model
Python
Jupyter Notebooks
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Data science, as a field, combines programming tools, statistical analysis, algorithms, and machine learning principles to extract meaningful insights from large amounts of information. It involves applying a variety of disciplines, including statistics, scientific methodologies, artificial intelligence (AI), and data analysis.
Some examples of careers in data science include:
Data analyst:A data analyst analyzes data and draws meaningful findings from their analysis. They help to build a clear image of the company's market position through data extraction utilizing high-tech computer models, data cleaning, and first-data analysis. They also assess data quality, plus they present their findings to management.
Data engineers:Data Engineers are the backbone of a company, for they control database design and management. They oversee the construction of data pipelines and ensure that data reaches the proper departments. They also collaborate with other data professionals and share findings with the enterprise via data visualization.
Business intelligence analyst:A business intelligence analyst analyzes data to help a firm become more efficient and profitable. They must be familiar with a wide range of specialized machines and tools. They also act as a bridge between business and technology, helping both improve performance.
Marketing analyst:A marketing analyst supports a company's marketing department. They undertake research and advise on what should be mass-produced and what should be discarded. Customer satisfaction surveys are also used to improve current products and services and to select new products to offer to target customers.
You will learn the significant steps involved in tackling a data science problem, and how to prepare and clean data. By completing a peer-reviewed assignment, you will demonstrate your understanding of data science methodology by applying it to your defined problem.
Once you have completed The Data Science Method course, you will earn your IBM Certificate and you will be one step closer to earning IBM Professional Certification if you are working towards the IBM Data Science Professional Certificate Program.
IBM Certificate
06 Modules
01 Skills
01 Final exam
06 Quizzes
13 Videos
Data collection model
Python
Jupyter Notebooks
Subscribe to get the latest tech career trends, guidance, and tips in your inbox.