Ph.D., Data Scientist
Despite and influx in computing power and access to data over the last couple of decades, our ability to use data within the decision-making process is either lost or not maximized all too often. We do not have a strong grasp of the questions asked and how to apply the data correctly to resolve the issues at hand.
The purpose of this course is to share the methods, models and practices that can be applied within data science, to ensure that the data used in problem-solving is relevant and properly manipulated to address business and real-world challenges.
You will learn how to identify a problem, collect and analyze data, build a model, and understand the feedback after model deployment.
Advancing your ability to manage, decipher and analyze new and big data is vital to working in data science. By the end of this course, you will have a better understanding of the various stages and requirements of the data science method and be able to apply it to your own work.
Ph.D., Data Scientist
Earn your certificate
Once you have completed this course, you will earn your certificate.
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:
1. 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.
2. 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.
3. 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.
4. 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.