data-science-using-python

Data Science with Python Certification Training

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Last Update March 10, 2022
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About This Course

Ninjaz Academy’s Data Science Training with Python will enable you to learn Data Science concepts from scratch. This Data Science Python Course will also help you master important Python programming concepts such as data operations, file operations, object-oriented programming and various Python libraries such as Pandas, Numpy, Matplotlib essential for Data Science.

This Python for Data Science certification training course will also make you understand the various types of Machine Learning, Recommendation Systems and many more Data Science concepts, to help you get started with your Data Science career.

You’ll learn the end-to-end data science process, covering everything you need to know to derive value from complex data. By the end of the course, you will be able to communicate data insights effectively through data visualizations. For your capstone, you’ll put machine-learning models into production to address a real-world data challenge.

Key Features:

  • Flexible Schedule
  • Tailor Made Training
  • 24 x 7 Expert Support
  • Access to the Recorded Sessions
  • Course material prepared by SMEs
  • Get certified at an affordable price
  • 42 Hours Instructor-led Online Training
  • Get key resources from Ninjaz Academy
  • Expert Data Science Certified instructors across the globe
  • Data Science with Python sample papers to prepare for your certification exam

Learning Objectives

Data wranglingData exploration
Data visualization
Mathematical computing
Web scraping
Hypothesis building
Python programming concepts
NumPy and SciPy package
ScikitLearn package for Natural Language Processing

Requirements

  • The pre-requisites for Python Data Science course training includes the fundamental understanding of Computer Programming Languages. Fundamentals of Data Analysis practiced over any of the data analysis tools like SAS/R will be a plus. However, you will be provided with complimentary “Python Statistics for Data Science” as a self-paced course once you enroll for the Data Science with Python certification course.

Target Audience

  • Programmers, Developers, Technical Leads, Architects
  • Developers aspiring to be a ‘Machine Learning Engineer'
  • Analytics Managers who are leading a team of analysts
  • Business Analysts who want to understand Machine
  • Learning (ML) Techniques
  • Information Architects who want to gain expertise in
  • Predictive Analytics
  • 'Python' professionals who want to design automatic predictive models

Curriculum

114 Lessons

Introduction to Python

Overview of Python
The Companies using Python
Different Applications where Python is used
Discuss Python Scripts on UNIX/Windows
Values, Types, Variables
Operands and Expressions
Conditional Statements
Loops
Command Line Arguments
Writing to the screen

Sequences and File Operations

Deep Dive – Functions, OOPs, Modules, Errors and Exceptions

Introduction to NumPy, Pandas and Matplotlib

Data Manipulation

Introduction to Machine Learning with Python

Supervised Learning – I

Dimensionality Reduction

Supervised Learning – II

Unsupervised Learning

Association Rules Mining and Recommendation Systems

Reinforcement Learning

Time Series Analysis

Model Selection and Boosting

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