What is Data Science?

What is Data Science Course

About Data Science

Data science continues to evolve as one of the most challenging and in-demand career paths for skilled practitioners. Today, successful data practitioners understand that they must advance past

the traditional skills of analyzing large amounts of data, data mining, data processing, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.

 “The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it — that’s going to be a hugely important skill in the next decades.”

                           – Hal Varian, chief economist at Google web

These skills are needful in almost all types of industries, causing skilled data scientists to be increasingly valuable to companies.

What Does a Data Scientist Do?

First, data scientists lay a solid data foundation in order to perform robust analytics. Then they use online experiments, among other methods, to achieve sustainable growth. In the end, they build machine learning pipelines and personalized data products to better understand their business and customers and to make better decisions. In other words, in tech, data science is about infrastructure, testing, machine learning for decision making, and data products.

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Applications of Data Science:

Data scientists have changed almost every industry. In medicine, their algorithms help predict patient side effects. In sports, their models and metrics have redefined “athletic potential.” Data science has even tackled traffic, with route-optimizing models that capture typical rush hours and weekend lulls. It is used in domains such as:

• Identifying and predicting disease
• Personalized healthcare recommendations
• Optimizing shipping routes in real-time
• Getting the most value out of soccer rosters
• Finding the next slew of world-class athletes
• Stamping out tax fraud
• Automating digital ad placement
• Algorithms that help you find love
• Predicting incarceration rates

(more on applications of Data Science)

About what is Data Science course

In this course, learner will be introduced to the data science professionals and will get an overview of what Data Science is today. This course will definitely provide you a detailed extraction of Data science.

Content included as below:

The what is data science course is also part of multiple programs:

• IBM Data Science Professional Certificate
• Key Technologies for Business Specialization
• Introduction to Data Science Specialization
• IBM AI Foundations for Business Specialization

About the tutor of this Course

Polong Lin a Data Scientist at IBM, with a focus on data science advocacy and partnerships. He is also a co-founder of a Data Science Bootcamp at IBM and currently leads Canada’s largest meetup group for data science in Toronto.

Alex Aklson, Ph.D. is a data scientist in the Digital Business Group at IBM Canada. They have been intensively involved in various exciting data science projects such as designing smart systems etc.

Syllabus – What you will learn from this course

In this what is data science course, you will be going through 3 weeks syllabus as:

(Overall content rating 96%)

Week 1:

Introduction

• The module includes fundamentals and paths to Data Science and advice for New Data Scientists.
• A concise introduction to Data Science Topics, Algorithms, and Cloud for Data Science.

Week 2:

Data Management Lessons and Exercises

In this module, learners would hear from the field experts on pursuing a career in this field. It will also cover the introductory part of data science and will have assignments at the end.

• Introduction on the foundation of Big Data and Hadoop.
• Acquiring Data science skills &Big Data.
• About Neural networks and Deep learning.
• Exercise for identifying objects in images with IBM Watson and Uploading and classification of your images.

Week 3:

Data Analytics and implementation

• You will conclude with Lesson summaries, report structures, and the pivotal role of Data Scientists in the industries.
• Future importance, applications, careers opportunities, and recruitment for Data Scientists.

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