How to grow as a data scientist after 2+ years of experience? #datascience #datasciencecareer

Data Science with Marco · Intermediate ·📐 ML Fundamentals ·3y ago

Key Takeaways

The video discusses career growth strategies for experienced data scientists, covering topics such as machine learning fundamentals, specialized skills, and industry trends.

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Playlist

Uploads from Data Science with Marco · Data Science with Marco · 26 of 38

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1 Linear Regression in Python | Data Science with Marco
Linear Regression in Python | Data Science with Marco
Data Science with Marco
 2 Classification in Python | logistic regression, LDA, QDA | Data Science With Marco
Classification in Python | logistic regression, LDA, QDA | Data Science With Marco
Data Science with Marco
 3 Resampling and Regularization | Data Science with Marco
Resampling and Regularization | Data Science with Marco
Data Science with Marco
 4 Decision Trees | Data Science with Marco
Decision Trees | Data Science with Marco
Data Science with Marco
 5 Suppor Vector Machine (SVM) in Python | Data Science with Marco
Suppor Vector Machine (SVM) in Python | Data Science with Marco
Data Science with Marco
 6 Unsupervised Learning | PCA and Clustering | Data Science with Marco
Unsupervised Learning | PCA and Clustering | Data Science with Marco
Data Science with Marco
 7 Data Science Portfolio Project: Regression #1 | Data Science with Marco
Data Science Portfolio Project: Regression #1 | Data Science with Marco
Data Science with Marco
 8 Data Science Portfolio Project: Regression #2 | Data Science with Marco
Data Science Portfolio Project: Regression #2 | Data Science with Marco
Data Science with Marco
 9 What Are Time Series - Applied Time Series Analysis in Python and TensorFlow
What Are Time Series - Applied Time Series Analysis in Python and TensorFlow
Data Science with Marco
 10 Basic Statistics - Applied Time Series Analysis in Python and TensorFlow
Basic Statistics - Applied Time Series Analysis in Python and TensorFlow
Data Science with Marco
 11 Autocorrelation and White Noise - Applied Time Series Analysis in Python and TensorFlow
Autocorrelation and White Noise - Applied Time Series Analysis in Python and TensorFlow
Data Science with Marco
 12 Stationarity and Differencing - Applied Time Series Analysis in Python and TensorFlow
Stationarity and Differencing - Applied Time Series Analysis in Python and TensorFlow
Data Science with Marco
 13 Random Walk Model - Applied Time Series Analysis in Python and TensorFlow
Random Walk Model - Applied Time Series Analysis in Python and TensorFlow
Data Science with Marco
 14 Moving Average Process - Applied Time Series Analysis in Python and TensorFlow
Moving Average Process - Applied Time Series Analysis in Python and TensorFlow
Data Science with Marco
 15 Autoregressive Process - Applied Time Series Analysis in Python and TensorFlow
Autoregressive Process - Applied Time Series Analysis in Python and TensorFlow
Data Science with Marco
 16 ARMA Model - Time Series Analysis in Python and TensorFlow
ARMA Model - Time Series Analysis in Python and TensorFlow
Data Science with Marco
 17 What is data science?
What is data science?
Data Science with Marco
 18 Answering DATA SCIENCE questions #1 - Why learn SQL when Python and R exist?
Answering DATA SCIENCE questions #1 - Why learn SQL when Python and R exist?
Data Science with Marco
 19 R vs Python in the Industry - Data Science Q&A #datascience #datasciencecareer #careeradvice
R vs Python in the Industry - Data Science Q&A #datascience #datasciencecareer #careeradvice
Data Science with Marco
 20 Data science or data engineering - which is best for you? #datascience #datasciencecareer
Data science or data engineering - which is best for you? #datascience #datasciencecareer
Data Science with Marco
 21 Where to find data for data science projetcs? #datascience #datasciencecareer
Where to find data for data science projetcs? #datascience #datasciencecareer
Data Science with Marco
 22 Data science certificates on resume? #datascience #datasciencecareer #careeradvice
Data science certificates on resume? #datascience #datasciencecareer #careeradvice
Data Science with Marco
 23 Should you aim for data science or data engineering? | Data Science Q&A #1
Should you aim for data science or data engineering? | Data Science Q&A #1
Data Science with Marco
 24 Don't waste time on this | #datascience #datasciencecareer
Don't waste time on this | #datascience #datasciencecareer
Data Science with Marco
 25 Low-code AI tools - are they good? | #datascience #datasciencecareer #careeradvice
Low-code AI tools - are they good? | #datascience #datasciencecareer #careeradvice
Data Science With Marco
 ▶ How to grow as a data scientist after 2+ years of experience? #datascience #datasciencecareer
How to grow as a data scientist after 2+ years of experience? #datascience #datasciencecareer
Data Science with Marco
 27 Transition into DATA SCIENCE without a masters or bootcamp #careertransition
Transition into DATA SCIENCE without a masters or bootcamp #careertransition
Data Science With Marco
 28 How to improve your data science profile?
How to improve your data science profile?
Data Science With Marco
 29 How to learn Python for data science?
How to learn Python for data science?
Data Science With Marco
 30 Does Scrum/Agile work for data science?
Does Scrum/Agile work for data science?
Data Science With Marco
 31 What are the major roles in analytics and how to choose?
What are the major roles in analytics and how to choose?
Data Science with Marco
 32 Thoughts and advice for a live SQL coding round
Thoughts and advice for a live SQL coding round
Data Science With Marco
 33 Data science interview question: difference between type 1 and type 2 error
Data science interview question: difference between type 1 and type 2 error
Data Science With Marco
 34 Feature selection in machine learning | Full course
Feature selection in machine learning | Full course
Data Science With Marco
 35 Anomaly detection in time series with Python | Data Science with Marco
Anomaly detection in time series with Python | Data Science with Marco
Data Science With Marco
 36 Podcast - TimeGPT, predicting the future, and more
Podcast - TimeGPT, predicting the future, and more
Data Science With Marco
 37 Big announcement - Revealing my new book
Big announcement - Revealing my new book
Data Science With Marco
 38 Get Started in Time Series Forecasting in Python | Full Course
Get Started in Time Series Forecasting in Python | Full Course
Data Science With Marco

This video provides guidance on how to advance as a data scientist after gaining 2+ years of experience, focusing on enhancing machine learning skills and staying updated with industry trends.

Key Takeaways
  1. Stay updated with industry trends and advancements
  2. Enhance machine learning skills with specialized courses
  3. Explore new tools and technologies
  4. Network with peers and industry leaders
  5. Pursue advanced certifications or education
💡 Continuous learning and professional development are crucial for career growth as a data scientist.

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