Tutorials > Applied Data Science Specialization
Applied Data Science SpecializationDate: 12 April 2025 | Posted by: AD-TEAM |
![]() 561.57 MB | 00:13:31 | mp4 | 1280X720 | 16:9 Genre:eLearning |Language:English Files Included : 01 project-scenario-and-overview.mp4 (5.64 MB) 01 data-collection-overview.mp4 (7.09 MB) 01 data-wrangling-overview.mp4 (4.71 MB) 01 exploratory-data-analysis-overview.mp4 (2.93 MB) 01 interactive-visual-analytics-and-dashboards.mp4 (4.18 MB) 01 predictive-analysis-overview.mp4 (1.8 MB) 01 elements-of-a-successful-data-findings-report.mp4 (7.52 MB) 02 best-practices-for-presenting-your-findings.mp4 (4.94 MB) 01 course-introduction.mp4 (4.45 MB) 02 understanding-the-data.mp4 (4.24 MB) 03 python-packages-for-data-science.mp4 (3.2 MB) 04 importing-and-exporting-data-in-python.mp4 (6.26 MB) 05 getting-started-analyzing-data-in-python.mp4 (6.44 MB) 06 accessing-databases-with-python.mp4 (5.03 MB) 01 pre-processing-data-in-python.mp4 (3.06 MB) 02 dealing-with-missing-values-in-python.mp4 (7.83 MB) 03 data-formatting-in-python.mp4 (4.8 MB) 04 data-normalization-in-python.mp4 (4.89 MB) 05 binning-in-python.mp4 (2.59 MB) 06 turning-categorical-variables-into-quantitative-variables-in-python.mp4 (2.84 MB) 01 exploratory-data-analysis.mp4 (1.96 MB) 02 descriptive-statistics.mp4 (6.3 MB) 03 groupby-in-python.mp4 (4.62 MB) 04 correlation.mp4 (3.66 MB) 05 correlation-statistics.mp4 (3.62 MB) 01 model-development.mp4 (2.79 MB) 02 linear-regression-and-multiple-linear-regression.mp4 (8.95 MB) 03 model-evaluation-using-visualization.mp4 (6.38 MB) 04 polynomial-regression-and-pipelines.mp4 (6.24 MB) 05 measures-for-in-sample-evaluation.mp4 (6.11 MB) 06 prediction-and-decision-making.mp4 (6.98 MB) 01 model-evaluation-and-refinement.mp4 (9.95 MB) 02 overfitting-underfitting-and-model-selection.mp4 (5.78 MB) 03 ridge-regression.mp4 (5.54 MB) 04 grid-search.mp4 (6.6 MB) 01 types.mp4 (3.95 MB) 01 expressions-and-variables.mp4 (5.17 MB) 01 string-operations.mp4 (5.92 MB) 01 list-and-tuples.mp4 (11.63 MB) 01 dictionaries.mp4 (4.2 MB) 01 sets.mp4 (7.18 MB) 01 conditions-and-branching.mp4 (13.3 MB) 01 loops.mp4 (8.82 MB) 01 functions.mp4 (17.83 MB) 01 exception-handling.mp4 (5.46 MB) 01 objects-and-classes.mp4 (14.23 MB) 01 reading-files-with-open.mp4 (4.92 MB) 02 writing-files-with-open.mp4 (4.34 MB) 01 loading-data-with-pandas.mp4 (4.43 MB) 02 pandas-working-with-and-saving-data.mp4 (2.97 MB) 01 one-dimensional-numpy.mp4 (13.96 MB) 02 two-dimensional-numpy.mp4 (9.5 MB) 01 simple-apis-part-1.mp4 (7.59 MB) 02 simple-apis-part-2.mp4 (2.31 MB) 01 rest-apis-http-requests-part-1.mp4 (5.71 MB) 02 rest-apis-http-requests-part-2.mp4 (6.74 MB) 03 optional-html-for-webscraping.mp4 (7.17 MB) 04 webscraping.mp4 (7.48 MB) 05 working-with-different-file-formats-csv-xml-json-xlsx.mp4 (5.7 MB) 01 welcome-to-the-course.mp4 (5.27 MB) 01 overview-of-data-visualization.mp4 (10.45 MB) 02 types-of-plots.mp4 (11.43 MB) 03 plot-libraries.mp4 (8.18 MB) 04 introduction-to-matplotlib.mp4 (8.97 MB) 05 basic-plotting-with-matplotlib.mp4 (5.96 MB) 06 dataset-on-immigration-to-canada.mp4 (4.55 MB) 07 line-plots.mp4 (5.71 MB) 01 area-plots.mp4 (7.69 MB) 02 histograms.mp4 (6.53 MB) 03 bar-charts.mp4 (4.76 MB) 01 pie-charts.mp4 (4.74 MB) 02 box-plots.mp4 (3.71 MB) 03 scatter-plots.mp4 (5.01 MB) 04 plotting-directly-with-matplotlib.mp4 (11.81 MB) 01 waffle-charts-word-cloud.mp4 (7.54 MB) 02 seaborn-and-regression-plots.mp4 (6 MB) 01 introduction-to-folium.mp4 (4.33 MB) 02 maps-with-markers.mp4 (8.07 MB) 03 choropleth-maps.mp4 (6.67 MB) 01 dashboarding-overview.mp4 (6.01 MB) 03 introduction-to-plotly.mp4 (7.94 MB) 01 introduction-to-dash.mp4 (4.95 MB) 03 make-dashboards-interactive.mp4 (7.62 MB) 05 understanding-the-lab-environment.mp4 (12.15 MB) 02 html-for-webscraping.mp4 (7.12 MB) 03 webscraping.mp4 (7.48 MB)] Screenshot ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() See full article |