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How do I Learn Data Science?

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1

1

$begingroup$

I am a Web Developer, looking for a career switch from being a web developer to a data scientist. Looked for various online and offline courses, didn't find an appropriate flow of studying or resources. Can anyone guide me on how to make this shift in career path?

machine-learning career

share|improve this question

edited 52 secs ago

Ethan

470220

asked 11 hours ago

G Satish KumarG Satish Kumar

61

New contributor

G Satish Kumar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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1

1

$begingroup$

I am a Web Developer, looking for a career switch from being a web developer to a data scientist. Looked for various online and offline courses, didn't find an appropriate flow of studying or resources. Can anyone guide me on how to make this shift in career path?

machine-learning career

share|improve this question

edited 52 secs ago

Ethan

470220

asked 11 hours ago

G Satish KumarG Satish Kumar

61

New contributor

G Satish Kumar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

I am a Web Developer, looking for a career switch from being a web developer to a data scientist. Looked for various online and offline courses, didn't find an appropriate flow of studying or resources. Can anyone guide me on how to make this shift in career path?

machine-learning career

share|improve this question

edited 52 secs ago

Ethan

470220

asked 11 hours ago

G Satish KumarG Satish Kumar

61

New contributor

G Satish Kumar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share|improve this question

edited 52 secs ago

Ethan

470220

asked 11 hours ago

G Satish KumarG Satish Kumar

61

New contributor

G Satish Kumar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

edited 52 secs ago

Ethan

470220

asked 11 hours ago

G Satish KumarG Satish Kumar

61

New contributor

G Satish Kumar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

edited 52 secs ago

Ethan

470220

edited 52 secs ago

Ethan

470220

asked 11 hours ago

G Satish KumarG Satish Kumar

61

New contributor

G Satish Kumar is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 11 hours ago

G Satish KumarG Satish Kumar

61

2 Answers
2

active

oldest

votes

1

$begingroup$

1. Build a foundation in the basic Mathematical/Statistical concepts that you will need to further understand the algorithms/topics that you are working with.

This includes: Calculus, Linear Algebra, Probability/Statistics (Some form of optimization my also be helpful for conceptual understanding)

2. Learn the code. Become familiar with Python (or R) and become proficient in the Python packages Pandas, Numpy, and Matplotlib




3. Become familiar with ML concepts conceptually. Go through Andrew Ng's Intro to Machine Learning Course (available for free here on Coursea).




4. Begin to implement ML algorithms with code. Become proficient in the Python package scikit-learn.




5. Once you are comfortable with these concepts move to more advanced topics like Neural Networks and Deep Learning. Learn packages like Keras and Tensorflow

(Note: This is just a basic workflow. Depending on what Data Science you hope to do may require additional skills. Production level systems leveraging big data may require additional knowledge of things like Hadoop or Spark etc.)

share|improve this answer

edited 8 hours ago

answered 8 hours ago

EthanEthan

470220

$endgroup$

add a comment | 

-1

$begingroup$

Go for AnalyticVidhya, Kaggle websites for Data sets. They have got the full blogs for the begineers.
Learn basic statistics, learn graph visualization.
Learn at least Python or R.
Watching a video of an hour might not help but you need to practice it a lot more.
Best of luck

share|improve this answer

answered 11 hours ago

BbkBbk

1

New contributor

Bbk is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

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1

$begingroup$

1. Build a foundation in the basic Mathematical/Statistical concepts that you will need to further understand the algorithms/topics that you are working with.

This includes: Calculus, Linear Algebra, Probability/Statistics (Some form of optimization my also be helpful for conceptual understanding)

2. Learn the code. Become familiar with Python (or R) and become proficient in the Python packages Pandas, Numpy, and Matplotlib




3. Become familiar with ML concepts conceptually. Go through Andrew Ng's Intro to Machine Learning Course (available for free here on Coursea).




4. Begin to implement ML algorithms with code. Become proficient in the Python package scikit-learn.




5. Once you are comfortable with these concepts move to more advanced topics like Neural Networks and Deep Learning. Learn packages like Keras and Tensorflow

(Note: This is just a basic workflow. Depending on what Data Science you hope to do may require additional skills. Production level systems leveraging big data may require additional knowledge of things like Hadoop or Spark etc.)

share|improve this answer

edited 8 hours ago

answered 8 hours ago

EthanEthan

470220

$endgroup$

add a comment | 

1

$begingroup$

1. Build a foundation in the basic Mathematical/Statistical concepts that you will need to further understand the algorithms/topics that you are working with.

This includes: Calculus, Linear Algebra, Probability/Statistics (Some form of optimization my also be helpful for conceptual understanding)

2. Learn the code. Become familiar with Python (or R) and become proficient in the Python packages Pandas, Numpy, and Matplotlib




3. Become familiar with ML concepts conceptually. Go through Andrew Ng's Intro to Machine Learning Course (available for free here on Coursea).




4. Begin to implement ML algorithms with code. Become proficient in the Python package scikit-learn.




5. Once you are comfortable with these concepts move to more advanced topics like Neural Networks and Deep Learning. Learn packages like Keras and Tensorflow

(Note: This is just a basic workflow. Depending on what Data Science you hope to do may require additional skills. Production level systems leveraging big data may require additional knowledge of things like Hadoop or Spark etc.)

share|improve this answer

edited 8 hours ago

answered 8 hours ago

EthanEthan

470220

$endgroup$

add a comment | 

$begingroup$

1. Build a foundation in the basic Mathematical/Statistical concepts that you will need to further understand the algorithms/topics that you are working with.

This includes: Calculus, Linear Algebra, Probability/Statistics (Some form of optimization my also be helpful for conceptual understanding)

2. Learn the code. Become familiar with Python (or R) and become proficient in the Python packages Pandas, Numpy, and Matplotlib




3. Become familiar with ML concepts conceptually. Go through Andrew Ng's Intro to Machine Learning Course (available for free here on Coursea).




4. Begin to implement ML algorithms with code. Become proficient in the Python package scikit-learn.




5. Once you are comfortable with these concepts move to more advanced topics like Neural Networks and Deep Learning. Learn packages like Keras and Tensorflow

(Note: This is just a basic workflow. Depending on what Data Science you hope to do may require additional skills. Production level systems leveraging big data may require additional knowledge of things like Hadoop or Spark etc.)

share|improve this answer

edited 8 hours ago

answered 8 hours ago

EthanEthan

470220

$endgroup$

share|improve this answer

edited 8 hours ago

answered 8 hours ago

EthanEthan

470220

answered 8 hours ago

EthanEthan

470220

answered 8 hours ago

EthanEthan

470220

-1

$begingroup$

Go for AnalyticVidhya, Kaggle websites for Data sets. They have got the full blogs for the begineers.
Learn basic statistics, learn graph visualization.
Learn at least Python or R.
Watching a video of an hour might not help but you need to practice it a lot more.
Best of luck

share|improve this answer

answered 11 hours ago

BbkBbk

1

New contributor

Bbk is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

-1

$begingroup$

Go for AnalyticVidhya, Kaggle websites for Data sets. They have got the full blogs for the begineers.
Learn basic statistics, learn graph visualization.
Learn at least Python or R.
Watching a video of an hour might not help but you need to practice it a lot more.
Best of luck

share|improve this answer

answered 11 hours ago

BbkBbk

1

New contributor

Bbk is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

Go for AnalyticVidhya, Kaggle websites for Data sets. They have got the full blogs for the begineers.
Learn basic statistics, learn graph visualization.
Learn at least Python or R.
Watching a video of an hour might not help but you need to practice it a lot more.
Best of luck

share|improve this answer

answered 11 hours ago

BbkBbk

1

New contributor

Bbk is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share|improve this answer

answered 11 hours ago

BbkBbk

1

New contributor

Bbk is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

answered 11 hours ago

BbkBbk

1

New contributor

Bbk is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

answered 11 hours ago

BbkBbk

1