Data science

1. Data Science Data Science

2. Data Science Google Trends Google NGRAM Data Science: interest by country Data Science Data Scientist Data Science Roadmap Data Science Programming Language

3. Data Science 0 20 40 60 80 100 120 Data Science: (Worldwide)

4. Data Science

5. Data Science 0 10 20 30 40 50 60 70 80 90 100 Data Science: interest by country

6. Data Science Data Engineer Data Analyst Software Math and Algorithms Computer Science Data

7. Data Science Mathematics Statistical Analysis Machine Learning Software Engineering Data Scientist

8. Data Science Python R Julia Java Scala C++

9. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

11. Data Science  Matrix  Linear Algebra  Binary Tree  Hash functions  Database basic  Multidimensional Data model  Relational Algebra 05%

13. Data Science  Descriptive statistics  Probability theorem  Random variables  Bayes theorem  Histograms  Continues distributions  ANOVA  Monte Carlo method  Kernel density  Regressions  Correlations  Euclidian distance  Least Fit 10%

15. Data Science  Variables  Vectors  Matrices  Array  List  Functions  Data frames  Python/R Basics  Manipulate Data frames  Install Packages 15%

17. Data Science  Supervised learning  Unsupervised learning  Training / Testing data  Classification  Linear Classifiers  Decision tree  Boosting  Naïve Bayes classifier 30%

18. Data Science  Regression  Linear Regression  Multiple Regression  Ridge Regression  Kernel Regression  Logistic Regression  Clustering  Nearest Neighbor  k-means  Hierarchical Clustering  Precision-Recall 30%

20. Data Science  Text analysis  Name entity recognition  Corpus  Market based analysis  Feature extraction  Using Mahout/UIMA  Using Weka  Using NLTK  Classify text 40%

22. Data Science  Data Exploration in R/Python  Uni, Bi & Multivariate Viz  ggplot2  Histogram & Pie (Uni)  Tree & Tree map  Scatter plot (Bi)  Line Charts (Bi) 50%

23. Data Science  Special Charts  Time line  Decision Tree  D3.js  Tableau  Matplotlib, vispy, bokeh, seaborn, pygal, folium, and networkx 50%

25. Data Science  Map reduce Fundamentals  Hadoop Components  HDFS  Data replication principles  Name and data nodes  Using Mahout  Cassandra  MongoDB 70%

27. Data Science  Data formats  Data discovery  Data sources  Data integration  Data fusion  Transformation  Data survey  Google OpenRefine 75%

29. Data Science  Dimensionality Reduction  Normalization  Data scrubbing  Handling missing values  Denoising  Feature Extraction  Sampling  Principle Component analysis 80%

31. Data Science  MS Excel  Python, R packages  Weka, Knime, RapidMiner  Hadoop, Spark, Storm  D3.js, ggplot2, Shiny, Matplotlib, Tableau  NLTK  WebScraper  scikit-learn, Theano, Keras  Cassandra, Mongo DB 100%

32. Data Science NumPy SciPy Matplotlib Pandas Scikit Learn Statsmodels Seaborn Scrapy Keras

33. Data Science facebook.com/mloey mohamedloey@gmail.com twitter.com/mloey linkedin.com/in/mloey mloey@fci.bu.edu.eg

Data science

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