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About Course:

Our Data Science with Python training course is aimed at analysts and software developers who need to create analysis and data visualization solutions using the key functions and libraries available in and around Python. You will benefit from extensive hands-on labs, delivered by an expert Data Science practitioner who can guide you from the basics of data wrangling with Python to using sophisticated libraries to visualize and make predictions based on your data. The Data Science with Python training course comprises two modules - Data Analysis with Python, and Machine Learning with Python, which can be taken individually - let us know if you would like to split your attendance of each module.


Duration : 30 hours

Fee: 299


Job Trends


Who Should Learn?
  • Any IT experienced Professional
  • Who wants to make a career in python web development
  • Software automation
  • Data Analytics
  • Fresh Graduates
  • Any B.E/ B.Tech/ BSC/ MCA/ M.Sc Computers/ M.Tech/ BCA/ B.Com College Students in any stream
Prerequisite

This certification training course does not presume or require any prior knowledge on Python for Data Science. 
To understand the concepts, useful to know basic knowledge of application. We are recommending that students have following:

  • Basic understanding of Computer Programming Languages

Delivery Methodology

We are using an experiential delivering methodology that blends theoretical concepts with hands-on practical learning to ensure a holistic understanding of the subject or course.

Class Delivery

Live Interactive classes with expert

Training Calender

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Contact Us

+91 769-409-5404

Includes
  • 24 hours on-demand video
  • Articles
  • Coding Exercises
  • Full lifetime access
  • Certificate of Completion

Curriculum

Python for Data Science

Data Science Analytics to the rescue

What is Data science and Data Mining?

  • Data science

It's a study of all information, where we represents and turns into valuable resource for business and their strategies.

  • Data Mining

Large amounts of structured and unstructured data to identify patterns can help an organization rein in costs, increase efficiencies, recognize new market opportunities and increase the organization's competitive advantage.

Why to learn Python for Data Science?
Generally, Employers looking for candidates to fill data scientist positions that have knowledge capabilities into: 

  • Experience with programming languages like Python, Perl, C/C++, and Java
  • Proficiency in big data software platforms like Hadoop
  • In-depth knowledge of at least a few analytical tools like SAS and R

Acquire new skills with our Python for Data Science

  • You can expert in developing predictive systems and creating efficient algorithms to improve data quality
  • Identifying, evaluating, designing, and implementing statistical analyses of gathered data to create analytic metrics and tools
  • Practicle knowledge over Designing, building, and deploying data analysis systems for large data sets
  • You can able to Create algorithms to extract information from large data sets
  • Efficiently deploying or establishing, automated processes for model development, validation, implementation, and large-scale data analysis
  • Developing metrics and prototypes used to drive business decisions
  • Identifying emergent trends and opportunities for future client growth and development

Course Overview
In this curriculum, you will learn about basic concepts of Python, how to use Python both interactively and through a script. You can Create your first variables and acquaint yourself with Python's basic data types, powerful ways to store and manipulate data as well as cool data science tools to start your own analyses. This Course will also help you in master of Python programming concepts such as data operations,  file operations, object-oriented programming and various Python libraries such as Pandas, Numpy, Matplotlib which are essential for Data Science.


Introduction to Python for Data Science Training Course Curriculum

Want to become an expert in Python for Data Science?

Introduction to Data science

  • Basics of Data Science
  • What is data science
  • AI vs DS vs Machine learning
  • Fields of data science
  • Applications of Data Science

Big Data

  • Definition of Big data
  • Applications of Big data
  • Hadoop and Spark

Hadoop

  • Map reduce
  • HDFS

Spark

  • Tools and language

Natural Language Processing

  • Definition of NLP
  • Application of NLP
  • Tools and Language

Machine learning

  • Definition of Machine learning
  • Types of Machine Learning
  • Applications of Machine learning
  • Tools and Languages

NoSQL Data bases

  • Definition
  • SQL vs NoSQL Databases
  • NoSQL databases tools
  • Search Engine technologies

Python Basics

             Installation

  •              Anaconda
  •             Environment creation
  •             Pycharm

Interpreter

Data types in Python

String data types

List

Dictionary

Tuple

Set

Functions

Classes

OOPS

  • Inheritance
  • Encapsulation

Abstraction

  • Exceptional handling

Numpy, Pandas

  • Numpy Tutorial
  • Pandas Tutorial

Natural Language Processing

  • Basics of NLP
  • Applications of NLP
  • Tokenization
  • Stopwords
  • Stemming and lemmatization
  • Part of Speech tagging
  • Named entity recognition
  • Custom NER system using OpenNLP (java)
  • Phrase Handling Application
  • Sentiment Analysis Application

Feature Extraction process

  • True/False model
  • Count Vectorizer
  • TF-IDF Vectorizer

Creating Model using NLTK Naïve Bayes algorithm

Recommendation System Application

Web Crawling

  • Scrapy Introduction
  • Xpath Introduction
  • Crawling Application

Machine learning

  • Basics of Machine Learning
  • Types of Machine Learning Algorithms

Supervised

Classification

  • Logistic Regression
  • K Nearest Neighbors
  • SVM
  • Decision Tree
  • Random Forest
  • Gradient Boosting
  • Naïve Bayes

Regression

  • Linear Regression
  • Polynomial Regression
  • SVR
  • Decision Tree Regressor
  • Random Forest Regressor

Unsupervised

Clustering

  • K Means Clustering
  • Hierarchical Clustering

Machine Learning Model Evaluation

  • Backward elimination Process
  • P value
  • R Squared

Class Delievery 

  • Live Interactive classes with expert

Delievery  Methodology
We are using an experiential delievering methodology that blends theoretical concepts with hands-on practical learning to ensure a holistic understanding of the subject or course

Use Case

Use Case 1

Certificate

Certificate
Benefits of Certificate

Certification demonstrates your dedication, motivation and technical knowledge on a specific platform. Having a certification shows that you not only possess comprehensive knowledge of that technology but you also care enough about your own career to spend the time and money to get the certification.

We are welcoming our Students or professionals to participate in our professional online courses. We are offering great variety of online training programs and professional courses that you can always find as desired. After the completion of training program they will receive a certificate from BISP. As a Certified professional you can apply that knowledge in your future profession and enjoy with better salaries & career prospects.

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