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- Exclusive lessons from Industry Experts
- Expert guidance & support
- Codekata – Gamified coding Arena
- MicroARC – Quick Quizzes to enhance your skill
- Internationally recognized accreditation

### Course Modules:

## Introduction to Data Engineering and Bigdata

## Introduction to Data Engineering and Bigdata

- 38 Exclusive Lessons
- 11 hrs
- English

- Introduction to Course
- Python Introduction and Installation
- Basic Syntax of Python
- Data Structures in Python
- Python Built-in Functions
- User Defined Functions in Python
- Modules and Packages in Python
- Introduction to Databases and MySQL Installation
- SQL-1
- SQL-2
- SQL-3
- SQL-4
- SQL Assignment
- Python Assignment
- Data Warehousing Concepts
- OLAP and its Operations
- Bigdata and Parallel Computing
- Hadoop and its Ecosystem
- HDFS Architecture and File Storage
- HDFS Installation and Commands
- HDFS Assignment
- Map Reduce and word count example
- Map Reduce Workflow
- Data Storage File Formats
- YARN
- Map Reduce Assignment
- Introduction to Apache Spark
- Spark Architecture and Toolkit
- Spark APIs : RDD
- Transformations and Actions
- Spark APIs: Distributed Shared Variables
- Spark APIs : Dataframes and Datasets
- Spark APIs : Spark SQL
- Spark Execution Modes
- Spark Application Life cycle and Tuning
- Spark Hands on Examples-1
- Spark Hands on Examples-2
- Spark Dataframe, RDD, Spark SQL Assignment

## R programming

## R programming

- 27 Exclusive Lessons
- 6 hrs
- English

- R - An Introduction
- Variables and Operators
- Vectors
- Matrices
- Lists
- Data Frames
- Factors and Datasets
- Summarise functions
- Conclusion
- Relational Operations
- Logical Operations
- Control Statements
- Looping Statements and Functions
- Mathematical and Statistical Relational Functions
- apply functions
- map functions
- Dplyr Select
- Dplyr - Slice, Mutate, Arrange
- data.table - Select, Filter and Sort
- Joins
- Grammar of Graphics
- Plots and Histograms
- Pie Charts
- ggplots
- Project Task
- Project Task Solution
- Final Assessment

## Data Analytics using Pandas

## Data Analytics using Pandas

- 16 Exclusive Lessons
- 3 hrs
- English

- Introduction
- Setting up Pandas Environment
- An Introduction to Jupyter Notebook
- Loading Data into Pandas
- A Deeper Look Into Data
- DataFrames - Basic Functions
- dataframes- rows and columns
- Sorting DataFrames
- Handling Datetime Fields in Pandas
- Statistical Functions in Pandas
- Pandas - Indexes
- Data Grouped Representation
- Data Visualization
- Adding New Data - Merge, Join
- Adding New Data - Append/Concat
- Final Project & End Note

## Data visualization with Matplotlib in Python

## Data visualization with Matplotlib in Python

- 34 Exclusive Lessons
- 7 hrs
- English

- Introduction to Matplotlib
- Installing Matplotlib and dependencies
- Setup - Jupyter Notebook
- Getting started with basic of Matplotlib
- Introduction to pyplot
- Adding Labels to plot
- Formatting plot style
- Specifying axis in plot
- Adding and customizing markers
- Adding Titles and Legends to a plot
- Scatter Plot and categorical plotting
- Scatter plot in matplotlib
- Plotting category categorical variables in various format
- Line and SETP method
- Assignment_1_Basics of Matplotlib
- Figure and Subplot in Matplotlib
- Concept of Figure and SubPlotting
- Plotting multiple figure and plots
- Applying Grids to the plot
- More Plots in Matplotlib
- Histograms in Matplotlib
- Bar charts in Matplotlib
- Pie Charts in Matplotlib
- Stack plots in Matplotlib
- Logarithmic plotting in Matplotlib
- Symlog and logit plot in Matplotlib
- Polar plot in Matplotlib
- Assignment_2_Intermediate knowledge of Matplotlib
- Working with Time-series data in matplotlib
- 3D Plotting and visualization in Matplotlib
- Working with Audio data in Matplotlib
- Working with images in matplotlib
- Saving plots as PNG and PDF file format in Matplotlib
- Assignment_3_Advance matplotlib knowledge

## Data visualization in python

## Data visualization in python

- 52 Exclusive Lessons
- 17 hrs
- English

- Introduction to Data Visualization
- Matplotlib for Data Visualization
- Using Matplotlib to draw plots
- Assignment on OO & Pyplot style in Matplotlib
- Visualizing & Customizing Plot appearances using Matplotlib
- Assignment on Plotting Basic plots using Matplotlib
- Multiple Line PLots
- Assignment on Drawing Multiple Line Plots
- Basics of Time Series Plotting
- Assignment on Time Series Plotting
- Time Series Plotting and adding styles to the plots
- Slicing and Customizing Time Series Data
- Assignment on Time Series slicing and plotting
- Twin Axes Plotting
- Bar Plot and Box Plots
- Assignment on Bar and Box Plots
- Voilin, Histogram and Scatter
- Assignment on Histogram and Scatter Plot
- Contour Plot and Annotations in Matplotlib
- Advance Annotations
- Assignment on annotations
- Image Tutorial in matplotlib
- Assignment on Image Tutorial
- Introduction to Seaborn Library
- Relational Plots and Subplots in Seaborn
- Subplotting in Rows and Columns using Relational Plot
- Assignment on Relational Plots in Seaborn
- Line Plots in Seaborn
- Assignment on Line Plots in Seaborn
- Bar Plots, Box Plots and Point Plots in Seaborn
- Assignment on Bar, Box and Line Plot
- Colour Palettes in Seaborn
- Introduction to BOKEH
- Assignment on Line and Bar Plotting in Bokeh
- Patch Plots and Scatter Marks in Bokeh
- Assignment on Patch Plots and Scatter Markers
- Area Plots and Circle Glyphs in Bokeh
- Assignment on Area Plots
- Rectangle, Oval and Polygon Glyphs in Bokeh
- Assignment on Rectangle, Oval and Polygon Glyphs
- Wedges, Arcs and Specialized curves in Bokeh
- Assignment on wedges, arcs and specialized curves in Bokeh
- Setting Plot ranges and Axes in Bokeh Plots
- Categorical and Log Axes in Bokeh
- Assignment on Bar plotting in Bokeh
- Twin Axes, Datetime axes and Annotations in Bokeh Plots
- Assignment on Twin, Datetime Axes
- Row and Column Layouts in Bokeh Plots
- Customizing Tools and Legends in Bokeh Plots
- Assignment on layout and Grid Plotting
- Column Data Source and Adding Widgets to Bokeh Plots
- Assignment on widgets in Bokeh Plots

## Machine Learning 101

## Machine Learning 101

- 17 Exclusive Lessons
- 3 hrs
- English

- About Machine Learning Course
- Installation of Anaconda
- What is Machine Learning
- Types of Machine Learning, Supervised Learning and Regression
- Types of ML,Logistic Regression and Unsupervised Learning
- SVM -What is SVM and How do they work
- SVM-Loading and Examining our dataset
- SVM-Building and Tweaking our SVM Classification mode
- What is Decision Tree?
- Building the Decision Tree : Decision Tree Learning
- Building a Decision Tree - Information Gain a Gini Impurity
- Decision Tree Lab:Building our First Decision Tree
- Decision Tree Lab:Viewing and Tweaking our Decision Tree
- What is Overfitting
- Random Forest Lab
- Teamwork
- Avoiding Overfitted Models

## PowerBI Step by Step

## PowerBI Step by Step

- 5 Exclusive Lessons
- 3 hrs
- English

### Certificate

- Certificate will generate only after successful completion of course
- Certificate is generated for every course individually
- Certificates are auto generated

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