8 Myths of Data Science
1. Data Science is all about tools and technologies
2. You need a PhD degree to become a Data Scientist
3. Only engineering graduates can become Data Scientists
4. Only statisticians can become Data Scientists
5. Paid offline Data Science courses are better than free online ones
6. Complex models are always better than simple ones
7. Communication and storytelling are not important in Data Science
8. Domain knowledge is not important for Data Science
Don’t believe in any of these myths.
Data Science is all about solving a problem using “data” in a “scientific” way.
Tools and technologies are secondary.
Your skills and experiences matter the most. Learn as much as you can - there
are enough free online courses.
Practising whatever you learn is very important. For example, if you’re learning
Python, install Python and practise whatever you learn.
Once you’re comfortable with the basics, apply your skills on real-life
projects. Participate in contests and hackathons.
SHARE and TAG others so that others can also learn.
#DataScienceWithDrAngshu #DataScience #Analytics #BigData #MachineLearning
#ArtificialIntelligence #Data #DataAnalytics #Python #SQL #Statistics
#DataVisualisation #Interview #Job
Follow Dr. Angshuman Ghosh (Ph.D., MBA, BE)
1. Data Science is all about tools and technologies
2. You need a PhD degree to become a Data Scientist
3. Only engineering graduates can become Data Scientists
4. Only statisticians can become Data Scientists
5. Paid offline Data Science courses are better than free online ones
6. Complex models are always better than simple ones
7. Communication and storytelling are not important in Data Science
8. Domain knowledge is not important for Data Science
Don’t believe in any of these myths.
Data Science is all about solving a problem using “data” in a “scientific” way.
Tools and technologies are secondary.
Your skills and experiences matter the most. Learn as much as you can - there
are enough free online courses.
Practising whatever you learn is very important. For example, if you’re learning
Python, install Python and practise whatever you learn.
Once you’re comfortable with the basics, apply your skills on real-life
projects. Participate in contests and hackathons.
SHARE and TAG others so that others can also learn.
#DataScienceWithDrAngshu #DataScience #Analytics #BigData #MachineLearning
#ArtificialIntelligence #Data #DataAnalytics #Python #SQL #Statistics
#DataVisualisation #Interview #Job
Follow Dr. Angshuman Ghosh (Ph.D., MBA, BE)