What is Data Science? Course by IBM

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Product is rated as #10 in category Data Science
Learner rating9.4
Content rating9.6

What is data science course IBM, introduces you to Industry professionals. This course will definitely provide you a detailed extraction of Data science.

Last updated on January 29, 2021 10:01 pm

Data Science

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 needed 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.

(more on Data Scientist)

Applications

Data Science applications

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, learners will be introduced to industry professionals and will get an overview of the Topic. This course will definitely provide you a detailed extraction of Data science.

This course is also part of multiple programs:

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 Scientists 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 projects such as designing smart systems etc.

Syllabus on What is Data Science Course?

In this course, you will be going through 3 weeks syllabus as:

(Overall content rating 96%)

Week 1

Introduction on What is Data Science?

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

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 and will have assignments at the end.

  • Introduction on the foundation of Big Data and Hadoop.
  • Acquiring Data science skills and 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, career opportunities, and recruitment for Data Scientists.

Note: Your review matters

If you have already done this course, kindly drop your review in our reviews section. It would help others to get useful information and better insight into the course offered.

FAQ

$38.00

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  • Coursera
  • IBM
  • Online Course
  • Self-paced
  • Beginner
  • Less Than 24 Hours
  • Free Course (Affordable Certificate)
  • English
  • Data Science Deep learning Hadoop
Expert Score
9.4
Learner rating
9.4
Content rating
9.6
PROS: Perfect for absolute beginners. Practical implementation and application. of concept. Interesting experiences shared by Data scientist professionals. Simplified content & easily understandable.
CONS: Very basic information Lengthy introductory content

Description

Data Science

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 needed 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.

(more on Data Scientist)

Applications

Data Science applications

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, learners will be introduced to industry professionals and will get an overview of the Topic. This course will definitely provide you a detailed extraction of Data science.

This course is also part of multiple programs:

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 Scientists 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 projects such as designing smart systems etc.

Syllabus on What is Data Science Course?

In this course, you will be going through 3 weeks syllabus as:

(Overall content rating 96%)

Week 1

Introduction on What is Data Science?

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

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 and will have assignments at the end.

  • Introduction on the foundation of Big Data and Hadoop.
  • Acquiring Data science skills and 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, career opportunities, and recruitment for Data Scientists.

Note: Your review matters

If you have already done this course, kindly drop your review in our reviews section. It would help others to get useful information and better insight into the course offered.

FAQ

Specification:

  • Coursera
  • IBM
  • Online Course
  • Self-paced
  • Beginner
  • Less Than 24 Hours
  • Free Course (Affordable Certificate)
  • English
  • Data Science Deep learning Hadoop

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What is Data Science? Course by IBM
What is Data Science? Course by IBM

$38.00

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