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

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
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
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 24 March, 2017
Application Last Date : 24 March, 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