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Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Data science is the same concept as data mining and big data. Data science is a concept to unify statistics, data analysis, machine learning, and their related methods in order to understand and analyze actual phenomena with data. The American Statistical Association identified database management, statistics, and machine learning, and distributed and parallel systems as the three emerging foundational professional communities.

If you are interested to learn Data Science from **Best Data Science Training Institute in Marathahalli,** then RIA Institute is the Right place. You can Register or Contact us to get updated about the new batch.

### Complete Data Science Course

#### INTRODUCTION

- Need of Data analyses
- Need of Statistics
- How Visualization helps Industry?
- How models helps to predict and find the pattern in it
- Data Science tools in market
- Why Python/R for Statistics & Data science?
- Who analyze data?
- Sample vs Population
- Descriptive & Inferential statistics
- Central tendency (Mean, Median, Mode)
- Standard deviation, variance, Quartiles, Box Plot
- Hypothesis testing
- Normal distribution, uniform distribution
- Histogram, frequency distribution
- Poisson distribution
- P-value, Z-test, T-test, F distribution
- Type 1 and 2 errors
- Chi square test
- Annova Analyses
- R-Square, Adjusted R-Square

#### Statistics

#### Spotfire

#### CHARTS

- Table visualization
- Cross Table
- Graphical table
- Bar chart
- Waterfall chart
- Line chart
- Combination chart
- Pie chart
- Scatter plot
- 3D Scatterplot
- Map chart
- Tree Map
- Heat Map
- KPI Chart
- Parallel co-ordinate plot
- Summary Table
- Information designer
- Data source
- IL’s – (prompts, parameterized, personalized)
- Joins
- Procedures
- Library Management
- GUID Export/import elements
- Text Area
- Data table/column/document properties
- Data on demand
- Markings, Calculated columns, Transformations
- Filters (types, schemas, filter functions)
- Details on Demand
- Tags, Lists, Bookmarks, Collaboration
- Webpage, Recommended visualizations
- Export visualizations
- Basics of Python
- Anaconda tool
- Spyder & Jupyter Notepad
- Arrays
- Dataframes
- Visualizations
- Pandas
- Numpy
- Matplotlib
- Seaborn
- All Packages related to Data science.
- Basics of R
- R Studio tool
- Vectors
- Lists
- Matrices
- Arrays
- Factors
- Data frames
- Visualizations
- All packages related to Data Science

**FEATURES**

**Python Or / And R**

PYTHON

PYTHON

**R**