Drive your career in Data Science forward | Data Science | IBM

 Drive your career in Data Science forward.

What is Data Science:

Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning, and big data.

Pros and Cons of Data Science – Why Choose Data Science for Your Career

Pros: 

1. Data Science is greatly in demand.

2. Data Science is a vastly abundant field and has a lot of opportunities.

3. Data Science is a vastly abundant field and has a lot of opportunities.

4. Data Science is a very versatile field. 

5. Data Science deals with enriching data and making it better for their company.

6. Data Scientists allow companies to make smarter business decisions.

7. Data Science has helped various industries to automate redundant tasks

8. Data Science Can Make You A Better Person'

Cons:

1. Data Science is Blurry Term

2. Mastering Data Science is near to impossible

'3. A large Amount of Domain Knowledge Required

4. Arbitrary Data May Yield Unexpected Results

5. Problem of Data Privacy

What you will learn:

1. Apply various Data Science and Machine Learning skills, techniques, and tools to complete a project and publish a report.

2. Practice with various tools used by Data Scientists and become experienced in using some of them like Jupyter notebooks.

3. Master the key steps involved in tackling a data science problem and learn to follow a methodology to think and work like a Data Scientist.

4. Write SQL to query databases and explore relational database concepts.

5. Understand Python and practice Python programming using Jupyter.

6. Import and clean data sets, analyze data, build and evaluate data models and pipelines using Python.

7. Utilize several data visualization tools, techniques, and libraries in Python to present data visually.

8. Understand and apply variously supervised and unsupervised Machine Learning models and algorithms to address real-world challenges using Python.

What is the Purpose of Data Science? 

1. Data Science for Better Marketing

2. Data Science for Customer Acquisition

3. Data Science for Innovation

4. Data Science for Enriching Lives