Discover the most searched Data Science related terms and optimize your content for maximum reach. Whether you’re a blogger, a webmaster or a seo pro, understanding popular Data Science keywords is crucial for connecting with your target audience.
Why Data Science Keywords Matter :
- Boost your SEO: Incorporate relevant keywords to improve your search engine rankings.
- Create engaging content: Use popular search terms to craft content that resonates.
- Enhance marketing strategies: Tailor your campaigns to match what your audience is actively searching for.
Explore Top Data Science Keywords
Below, you’ll find a curated list of the most searched keywords in the Data Science niche, along with their global monthly search volume and CPC on Google.
| Keyword | Search Volume | CPC |
|---|---|---|
| cnn | 20400000 | 2.00 |
| github | 823000 | 5.00 |
| hive | 550000 | 1.38 |
| pandas | 550000 | 2.00 |
| python | 368000 | 4.25 |
| aws | 301000 | 100.00 |
| power bi | 201000 | 27.00 |
| azure | 201000 | 26.70 |
| tableau | 201000 | 35.00 |
| sql | 165000 | 7.76 |
| big data | 165000 | 7.75 |
| artificial intelligence | 135000 | 3.38 |
| docker | 135000 | 100.00 |
| data analyst | 135000 | 12.23 |
| data analytics | 135000 | 12.23 |
| spark | 135000 | 1.07 |
| blockchain | 110000 | 4.10 |
| mongodb | 110000 | 13.57 |
| git | 110000 | 3.18 |
| algorithm | 110000 | 3.15 |
| statistics | 110000 | 2.69 |
| confidence interval | 110000 | 5.24 |
| google cloud | 110000 | 100.00 |
| gitlab | 90500 | 4.79 |
| kubernetes | 90500 | 3.71 |
| regression | 90500 | 0.00 |
| kafka | 90500 | 5.00 |
| jupyter notebook | 74000 | 2.82 |
| quantum computing | 74000 | 16.93 |
| kaggle | 74000 | 3.03 |
| pca | 74000 | 10.00 |
| data science | 74000 | 9.25 |
| data scientist | 74000 | 9.25 |
| devops | 60500 | 10.68 |
| normal distribution | 60500 | 0.00 |
| p-value | 49500 | 2.03 |
| t-test | 49500 | 2.90 |
| business analyst | 49500 | 9.30 |
| machine learning | 49500 | 6.88 |
| bitbucket | 49500 | 0.80 |
| poisson distribution | 49500 | 0.00 |
| binomial distribution | 49500 | 1.83 |
| pytorch | 49500 | 4.49 |
| linear regression | 40500 | 4.52 |
| tensorflow | 40500 | 5.23 |
| anova | 40500 | 11.31 |
| neural networks | 33100 | 5.02 |
| logistic regression | 33100 | 6.60 |
| chi-square test | 33100 | 0.00 |
| cloud computing | 33100 | 25.00 |
| clustering | 33100 | 1.09 |
| iot | 33100 | 6.06 |
| etl | 33100 | 10.28 |
| ci/cd | 33100 | 7.79 |
| data mining | 27100 | 17.10 |
| gan | 27100 | 3.58 |
| cassandra | 27100 | 8.32 |
| decision trees | 27100 | 15.04 |
| hadoop | 22200 | 9.72 |
| statistical significance | 22200 | 0.00 |
| numpy | 22200 | 4.29 |
| data engineer | 22200 | 11.69 |
| data visualization | 22200 | 11.33 |
| xgboost | 18100 | 5.01 |
| deep learning | 18100 | 5.75 |
| natural language processing | 18100 | 5.03 |
| classification | 18100 | 5.83 |
| scikit-learn | 18100 | 4.89 |
| r programming | 18100 | 9.43 |
| data lake | 18100 | 7.79 |
| data warehouse | 18100 | 7.27 |
| reinforcement learning | 14800 | 4.53 |
| business intelligence | 14800 | 8.83 |
| data governance | 14800 | 19.48 |
| svm | 14800 | 0.00 |
| data modeling | 14800 | 8.07 |
| hypothesis testing | 14800 | 3.33 |
| random forest | 12100 | 0.00 |
| lstm | 12100 | 4.82 |
| computer vision | 12100 | 5.58 |
| data management | 12100 | 43.70 |
| edge computing | 12100 | 7.80 |
| a/b testing | 12100 | 19.06 |
| predictive analytics | 12100 | 9.10 |
| nosql | 12100 | 12.66 |
| sentiment analysis | 9900 | 5.97 |
| data integration | 9900 | 47.63 |
| data cleaning | 8100 | 12.10 |
| mlops | 8100 | 9.08 |
| knn | 8100 | 10.48 |
| keras | 8100 | 2.23 |
| machine learning engineer | 6600 | 9.81 |
| time series analysis | 6600 | 6.29 |
| f-test | 6600 | 0.00 |
| data architecture | 6600 | 15.00 |
| data pipeline | 6600 | 9.68 |
| naive bayes | 6600 | 0.00 |
| data architect | 6600 | 15.00 |
| data privacy | 5400 | 11.42 |
| rnn | 5400 | 1.50 |
| data science certification | 5400 | 16.96 |
| transfer learning | 5400 | 5.64 |
| data science bootcamp | 5400 | 22.90 |
| data storytelling | 5400 | 6.48 |
| version control | 4400 | 5.87 |
| data security | 4400 | 25.00 |
| data science degree | 4400 | 20.04 |
| data quality | 3600 | 54.17 |
| gradient boosting | 3600 | 0.00 |
| feature engineering | 3600 | 6.70 |
| lightgbm | 3600 | 0.00 |
| data-driven decision making | 2900 | 19.28 |
| bayesian optimization | 2900 | 0.00 |
| dimensionality reduction | 2400 | 0.00 |
| data annotation | 2400 | 21.45 |
| data science interview questions | 2400 | 5.48 |
| data literacy | 2400 | 4.76 |
| explainable ai | 2400 | 5.40 |
| data labeling | 1900 | 25.71 |
| hyperparameter tuning | 1900 | 3.26 |
| data strategy | 1900 | 15.60 |
| chief data officer | 1900 | 16.66 |
| data augmentation | 1900 | 13.35 |
| grid search | 1900 | 0.00 |
| catboost | 1900 | 0.00 |
| data science career | 1900 | 10.57 |
| data science berkeley | 1900 | 25.67 |
| responsible ai | 1600 | 6.59 |
| feature selection | 1600 | 0.00 |
| data science resume | 1600 | 4.61 |
| ai researcher | 1600 | 6.00 |
| data science online courses | 1300 | 25.54 |
| data sampling | 1300 | 3.22 |
| data distribution | 1300 | 11.00 |
| ensemble learning | 1300 | 9.32 |
| data preprocessing | 1300 | 10.86 |
| ai regulation | 1000 | 45.06 |
| data ethics | 1000 | 3.07 |
| ethics in ai | 880 | 6.48 |
| data science reddit | 880 | 8.54 |
| random search | 880 | 0.00 |
| data science coursera | 880 | 12.43 |
| data science stanford | 880 | 21.08 |
| data science harvard | 880 | 11.53 |
| data science consultant | 880 | 15.43 |
| bias in ai | 720 | 4.78 |
| data science books | 720 | 7.91 |
| data science conferences | 720 | 8.56 |
| data science portfolio | 720 | 3.07 |
| ai governance | 590 | 8.00 |
| data version control | 480 | 7.82 |
| trustworthy ai | 480 | 6.83 |
| model deployment | 480 | 15.00 |
| model monitoring | 480 | 15.00 |
| data science linkedin | 390 | 11.05 |
| data culture | 390 | 8.71 |
| data science blogs | 320 | 5.65 |
| data science competitions | 320 | 7.17 |
| data science workflow | 320 | 8.53 |
| data science roles | 260 | 8.53 |
| data science ethics | 260 | 5.26 |
| data versioning | 210 | 0.00 |
| data science uber | 210 | 0.00 |
| data science lifecycle | 210 | 15.50 |
| data science edx | 210 | 6.60 |
| model interpretability | 170 | 0.00 |
| data science udacity | 140 | 14.61 |
| agile data science | 140 | 9.71 |
| data science amazon | 140 | 37.97 |
| data science podcasts | 110 | 0.28 |
| fairness in ai | 90 | 8.62 |
| data science datacamp | 90 | 4.13 |
| data science facebook | 90 | 0.00 |
| model versioning | 70 | 0.00 |
| data science airbnb | 70 | 18.73 |
| data science team structure | 70 | 8.53 |
| data science communities | 70 | 10.96 |
| data science stack exchange | 50 | 10.06 |
| data science netflix | 50 | 0.00 |
| data science best practices | 50 | 4.94 |
| data science medium | 40 | 10.53 |
| data science forums | 40 | 9.17 |
| data science stack overflow | 30 | 0.00 |
| scrum for data science | 30 | 0.00 |
| data science twitter | 30 | 0.00 |
| data science youtube channels | 20 | 17.00 |
| data science mit opencourseware | 10 | 0.00 |
| data science visual studio code | 10 | 0.00 |
| cross-validation | 10 | 0.00 |
| data science google | 10 | 0.00 |
| data science github | 10 | 0.00 |
| data science manager | 10 | 0.00 |
| data science quora | 10 | 0.00 |
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