It's all to do with the training: you can do a lot if you're properly trained.
An Institution That Can Change The Way of Your Life
It's all to do with the training: you can do a lot if you're properly trained.
An Institution That Can Change The Way of Your Life
It's all to do with the training: you can do a lot if you're properly trained.
An Institution That Can Change The Way of Your Life
It's all to do with the training: you can do a lot if you're properly trained.
An Institution That Can Change The Way of Your Life
It's all to do with the training: you can do a lot if you're properly trained.
An Institution That Can Change The Way of Your Life
It's all to do with the training: you can do a lot if you're properly trained.
An Institution That Can Change the Way of Your Life
It's all to do with the training: you can do a lot if you're properly trained.
An Institution That Can Change the Way of Your Life
It's all to do with the training: you can do a lot if you're properly trained.
An Institution That Can Change the Way of Your Life
It's all to do with the training: you can do a lot if you're properly trained.
An Institution That Can Change the Way of Your Life

Big Data Analytics with Python Language

This training program is jointly organized by TechnoBD Web Solution's Pvt Ltd & BITM.

 

" Big Data Analytics is the Top Ranked job of the 21st century - It has exciting work and incredible pay".

In Python for Data Analysis course, we assume students are already familiar with Python programming and they will learn advanced Python techniques useful for load, wrangling, cleaning, transformation and visualization of data. You will learn about SciPy, Numpy, Pandas and matplotlib package in this course.

 

  • What is this course about?

This course is tailored to impart knowledge on the fundamentals of data analysis and data-intensive applications using Python with Pandas and NumPy libraries.

Python is one of the most popular programming languages used for analyzing Big Data. Our training in Python will equip you to work with Big Data and gain better understanding of data analysis techniques.

 

  • Who will benefit from this course?

The booming demand for skilled data scientists across industries makes this course suited for all individuals at all level of experience. We recommend this data science training specially the following professionals:

  1. Software professionals looking for a career switch in the field of analytics
  2. Professionals working in field of Data and Business Analytics
  3. Graduates looking to build a career in Analytics and Data Science
  4. Anyone with a genuine interest in the field of Data Science
  • After completion of this training course, you will be able to:

This training has a clear focus on the vital concepts of business analytics and Python . By the end of the training, participants will be able to:

  1. Work on data exploration, data visualization, and predictive modeling techniques with ease.
  2. Gain fundamental knowledge on analytics and how it assists with decision making.
  3. Understand basic and advanced NumPy (Numerical Python) features
  4. Perform data analysis with tools in the Pandas library
  5. Manipulate, process, transform, merge and reshape large volumes of data
  6. Solve data analysis problems in web analytics, social sciences, finance, and economics
  7. Measure data by points in time, specific instances, fixed periods, or intervals

 

Training will be held in TechnoBD Web Solution's Pvt Ltd's Premises.

FEE - Tk 12,000

Prerequisite

There is no prerequisite knowledge. But if you have basic math skills and basic to Intermediate Python Skills is preferable.

 

  • I am from a non-technical background. Will I benefit from this course?

Yes, the course presents both the business and technical benefits of Big Data analytics and Data Visualization. The data mining and technical discussions are at a level that attendees with a business background can understand and apply. Where technical knowledge is required, sufficient guidance for all backgrounds is provided to enable activities to be completed and the learning objectives achieved.

Project Oriented Course

N/a

Course Outline

Day 01

Section 1: Intro to Course and Python

 
 

Course Intro

 

Note on Python.

Section 2: Setup

 
 

Installation Setup and Overview

 

IDEs and Course Resources

 

iPython/Jupyter Notebook Overview

Section 3: Learning Numpy

 
 

Intro to numpy

 

Creating arrays

 

Using arrays and scalars

 

Indexing Arrays

 

Array Transposition

 

Universal Array Function

 

Array Processing

 

Array Input and Output

Day 02

Section 4: Intro to Pandas

 
 

Series

 

DataFrames

 

Index objects

 

Reindex

 

Drop Entry

 

Selecting Entries

 

Data Alignment

 

Rank and Sort

 

Summary Statistics

 

Missing Data

 

Index Hierarchy

Section 5: Working with Data: Part 1

 
 

Reading and Writing Text Files

 

JSON with Python

 

HTML with Python

 

pip install beautifulsoup4

 

pip install lxml

 

Microsoft Excel files with Python

Section 6: Working with Data: Part 2

 
 

Merge

 

Merge on Index

 

Concatenate

 

Combining DataFrames

 

Reshaping

 

Pivoting

 

Duplicates in DataFrames

 

Mapping

 

Replace

 

Rename Index

 

Binning

 

Outliers

 

Permutation

Section 7: Working with Data: Part 3

 
 

GroupBy on DataFrames

 

GroupBy on Dict and Series

 

Aggregation

 

Splitting Applying and Combining

 

Cross Tabulation

Section 8: Data Visualization

 
 

Installing Seaborn

 

Histograms

 

Kernel Density Estimate Plots

 

Combining Plot Styles

 

Box and Violin Plots

 

Regression Plots

 

Heatmaps and Clustered Matrices

Section 9: Example Projects.

 
 

Data Projects Preview

 

Intro to Data Projects

 

Intro to Data Project - Stock Market Analysis

 

Data Project - Intro to Election Analysis

 

Titanic Project

Day 03

Section 10 : Regular Expression

 
 

Basic Patterns

 

Basic Examples

 

Repetition

 

Group Extraction

Section 11 : SciPy

 
 

Introduction

 

Basic functions

 

Special functions

 

Integration

 

Optimization

 

Interpolation

 

Fourier Transforms

 

Signal Processing

 

Linear Algebra

 

Sparse Eigenvalue Problems with ARPACK

 

Compressed Sparse Graph Routines

 

Spatial data structures and algorithms

 

Statistics

 

Multidimensional image processing

 

File IO

 

Weave

Section 12 : Exploratory analysis in Python using Pandas

 
 

Introduction to series and dataframes

 

Project - Loan Prediction Problem

   

Used Tools

N/a

COURSE SUMMARY

Course Duration : 3 Days
Total Hour : 12 Hours
Number of Batch : 1 Batch

Class Starting Tentative Date 10 February, 2017
Application Last Date : 10 February, 2017

Class Schedule

Day & Time : Friday 9:00 am - 1:00 pm
Duration : 4 hours per class

Project:

This will be discussed during the session


Certificate:

Certificate will be given after the course completion