Preloader images
Preloader icon

  • Comprehensive understanding of basic and advanced concepts, techniques and applications of Python in various business areas
  • Ease of integrating the core modeling process with database access, wrangling post-processing, such as visualization and web-serving
  • Cleaning up and preparing the data tables using Pandas along with It’s reusable and flexible code sharing features
  • Python frameworks and methods that can be used for routine operations of descriptive and inferential statistics
  • Matplotlib is the most widely used base library in Python for general visualization including how to usethis library for generating a box plot, bar chart, histogram, and pie diagram
  • NumPy is the de-facto standard for numerical computation in Python, used as the base for building more advanced libraries for data science and machine learning applications
  • Its integration with fast, compiled languages for numerical computation as used in NumPy and pandas
  • Experience sharing by industry experts form different business sectors 
  • Important skills for Fresher’s and working professionals to enhance their careers
  • Membership to KJA–KAALP Job Assistance program

70hrs

E – learning

Practice Datasets

& Case Studies

40+

Quizzes

Learn Anywhere

Anytime

Industry

Relevant

Webinars by

Industry Experts

Certification

by Kaalp

70hrs E-learning

Practice Datasets & Case Studies

40+ Quizzes

Learn Anywhere Anytime

Industry Relevant

Webinars by Industry Experts

Certification by Kaalp

Python is a general-purpose programming language which can be used for a wide spectrum of applications such as business data analysis, artificial intelligence and scientific computing.t is one of the most popular and powerful languages for data science used by most of the top companies like Facebook, Google, Yahoo, Amazon etc. Python is built on OOPS(Object Oriented Programming) and caters to a wide spectrum of analytical needs ranging from data access, data wrangling,munging, dashboards,visualizations & a comprehensive exposure to state of the art Machine Learning and Artificial Intelligence techniques. Python has more than 1Lakh libraries including DEEP learning API’s like Keras and Tensor flow which are the most sought after tools in the market. Python also has a web application framework called DJANGO which makes developing web application easy and fast.
Students from B.Sc, B.Com, BBA, Engineering and MBA disciplines who are looking for better employment opportunities. ​
Research scholars, academicians and scientists who wish use R for quantitative analysis and research projects. ​
Corporate professionals who wish to learn business analytics or pursue careers in data science. ​
Software and ITES professionals who wish to use R for data analysis and statistical modelling with advanced visualization and machine learning techniques. ​
  • Coding in Python along with exploring the various functionalities; This course will also introduce you to different Python IDE's like Spyder, Jupyter Notebook
  • This course also helps you to master Python operators, conditional statements, loop concepts data structures, built in operators &functions.
  • It will help you to understand the applications in Data Science by using Numpy, Pandas and visualizations using matplot lib
  • Further,in this course you shall learn about inferential statistics. You will also learn the various steps involved in hypothesis framing and hypothesis testing. By the end of this module you will be good at p- value approach to hypothesis testing.
  • The course covers extensively advanced statistical concepts including regression, forecasting & clustering techniques.
  • This module covers machine learning techniques-both supervised and unsupervised learning which helps you develop real time forecasting models to solve business problems.
Elementary knowledge of mathematics or statistics and basic programming skills will be an added advantage to those who attend this course. Exposure to SQL commands or Excel capabilities will be of added advantage.

Description

Python is a general-purpose programming language which can be used for a wide spectrum of applications such as business data analysis, artificial intelligence and scientific computing.t is one of the most popular and powerful languages for data science used by most of the top companies like Facebook, Google, Yahoo, Amazon etc. Python is built on OOPS(Object Oriented Programming) and caters to a wide spectrum of analytical needs ranging from data access, data wrangling,munging, dashboards,visualizations & a comprehensive exposure to state of the art Machine Learning and Artificial Intelligence techniques. Python has more than 1Lakh libraries including DEEP learning API’s like Keras and Tensor flow which are the most sought after tools in the market. Python also has a web application framework called DJANGO which makes developing web application easy and fast.

Who Should Attend?

Students from B.Sc, B.Com, BBA, Engineering and MBA disciplines who are looking for better employment opportunities. ​

Research scholars, academicians and scientists who wish use R for quantitative analysis and research projects. ​

Corporate professionals who wish to learn business analytics or pursue careers in data science. ​

Software and ITES professionals who wish to use R for data analysis and statistical modelling with advanced visualization and machine learning techniques. ​

WHAT YOU WILL LEARN

  • Coding in Python along with exploring the various functionalities; This course will also introduce you to different Python IDE's like Spyder, Jupyter Notebook
  • This course also helps you to master Python operators, conditional statements, loop concepts data structures, built in operators &functions.
  • It will help you to understand the applications in Data Science by using Numpy, Pandas and visualizations using matplot lib
  • Further,in this course you shall learn about inferential statistics. You will also learn the various steps involved in hypothesis framing and hypothesis testing. By the end of this module you will be good at p- value approach to hypothesis testing.
  • The course covers extensively advanced statistical concepts including regression, forecasting & clustering techniques.
  • This module covers machine learning techniques-both supervised and unsupervised learning which helps you develop real time forecasting models to solve business problems.

PREREQUISITES

Elementary knowledge of mathematics or statistics and basic programming skills will be an added advantage to those who attend this course. Exposure to SQL commands or Excel capabilities will be of added advantage.

Curriculum

This chapter provides a brief overview about Python programming language
  • History, Why Python?
In this module you will learn to install Python and set it up.
  • Environment Setup & Variables
  • Getting Python & Setting Path
You will learn the characteristics & salient features of Python
  • My first Python program
  • Identifiers
  • Reserved Words
  • Lines and Indentation
  • Command Line Arguments
In this chapter you will get introduced to a detailed study on various operations performed in Python
  • Arithmetic Operations & Number Methods
  • Accessing a value from Strings
  • Updating Strings & String Methods
  • Comparison & Assignment Operators
Understand how Lists, Tuples and Dictionaries are used in Python
  • Accessing, Updating & Deleting elements
This chapter covers the different types of loops & conditional statements
  • IF, ELSE statements & Nested IF statements
  • While, For, Break, Continue etc.

This chapter describes the various built-in functions & generators

In this chapter you will learn how data transformation is performed in Python
  • List processing & Conversions from 1 type to other

This topic covers simple & advanced regular expression to handle string data

This chapter covers various data accessing features in Python
  • Import Statement
  • Executing and Locating Modules
  • Exception Handling

This chapter provides various summary statistics like mean, median & mode with helps in data compression

In this chapter you will learn high level overview of the important libraries used in Data Science

This chapter describes step by step procedures to construct validate & test hypothesis needed for statistical analysis
  • Hypothesis Testing
  • Confidence Intervals
  • T-Test
  • Contingency Tables
  • Cross Tabs
  • Chi-Square significance test
  • Correlation
This chapter covers the different visualization techniques in Python
  • Bar
  • Line
  • Pie
  • Histogram

This chapter broadly describes various data munging & wrangling techniques using Pandas library

  • Importing and Exporting flat files
  • Operations on Pandas Data frames
  • Summary Statistics
  • Sub setting the Data frames
  • Handling missing values in the Data frames

This chapter introduces you to different Numpy libraries useful for handling quantitative data

The chapter details on high level overview on different machine learning techniques
  • Machine Learning with Supervised
  • Machine Learning with Unsupervised
  • Introduction to Deep Learning
The chapter describes various techniques used to segment data
  • Hierarchical Clustering
  • K-means
This chapter discusses the predictive modeling algorithms used to model multi-variate relationships in the data using Python
  • Simple Linear &  Multiple Linear Regression
  • Logistic Regression
The chapter explains three important algorithms to identify various profiles used in decision making
  • Decision trees
  • Random forest
  • Gradient Boosting

The chapter discusses the different techniques to model historical time series data using Python.

Preview

Level 1

Level 2

Testimonials

I completed the Introduction to Business Analytics training course conducted by Kaalp Consulting. The course material was easy to understand and I got hands on experience to practice the software commands. The instructors had good knowledge and gave us practical tips on application of analytics in problem solving. I was very satisfied with the training course.
BBA Student, Bangalore
Kaalp Consulting conducted a training program in R Programming for our institute. The course material is very extensive and well designed. The instructors were working professionals who have good experience in using R in business analytics. They explained the topics extremely well and gave us a good practical understanding on how R is used in real life scenarios. We very satisfied with the course and highly recommend it to others.
Lecturer and Trainer, TN.
Kaalp Consulting conducted a course on Introduction to Business Analytics with SQL, Excel and Tableau for our B.Com and BBA students. We were very pleased with the manner in which the courses were presented by their instructors who are industry professionals. The instructors explained the topics very well and shared their practical experience on how the business analytics is applied in real life. The course content is well designed and the program was managed very professionally by Kaalp Consulting. We have no hesitation in recommending them to any institution or individual who are interested in joining their training courses.
Dr. Geethu, KJC, Bangalore

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

Applications of "Python" in the Industry

Academia

Finance

Banking

Healthcare

Manufacturing

E-commerce

GET IN TOUCH



Our Story

Quest Skills has been founded by professionals with extensive experience in consulting, general management, HR and IT Services in international and multicultural business environments across several industry sectors.

Get In Touch

79/3A Sunny Brooks, Sarjapur Road, Bangalore 560035

info@questskills.com

+91-9148706970

Latest Posts

Copyright © 2019- 2020 QuestSkills Consulting  – Site Credit