Data Science With Python

Python Data Science Course in Singapore

Python for Data Science Certification Training Course

This Python Data Science course Singapore will start your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the basic concepts of Python programming and gain in-depth knowledge in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, start your career with this interactive, hands-on course and become master in python.

What are the course objectives?

The Data Science with Python course will furnish you with deep knowledge of the various libraries and packages required to perform data analysis, data visualization, web scraping, machine learning and natural language processing using Python.

Python programming has surpassed Java as the top language used to introduce US students to programming and computer science, and 46 percent of data science jobs list Python as a required skill.

After completing our training, the learner will be to:
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  • Download and analyze data programmatically
  • Learn techniques to deal with various data types such as ordinal, categorical, encoding
  • Learn data visualization
  • Understand Machine Learning
  • Learn predictive modelling tools and techniques
  • Discuss and validate Machine Learning algorithms
  • Explain Time Series and its related concepts
  • Perform Text Mining and Sentiment analysis

Why should you learn Data Science with Python to grow your career?

  • Most leading MNCs are investing in Data Science with Python and moreover, there is a constant increase in demand for professionals who can work in this technology.
  • Python’s design and libraries provide productivity over ten times compared to C, C++ or Java
  • A skilled Python Developer in the United States can earn $122,500 – indeed.com

Who should learn Data Science with Python?

The below job roles are benefited with our training:

  • BI Managers and Project Managers
  • Analytics Professionals
  • Software Developers and ETL Professionals
  • Big Data Professionals
  • Aspirants wishing to have a career in Python

What are the prerequisites for the Data Science with Python course?

There is no specific knowledge to learn Data Science with Python. Though, a basic programming knowledge can help.

What will you learn in this Data Science with Python training?

During the Data Science with Python course, you will be trained by our expert trainers and master in the following areas:

  • Concepts of Python for Data Science
  • OOP concepts, functions, and expressions
  • What is SQLite in Python, classes, and operations
  • Creating Pig and Hive UDF in Python
  • Deploy Python for MapReduce programming
  • Real-world Python for Data Science projects

Python for Data Science Certification Course Outline:

Lesson 01 - Data Science Overview

  • Introduction to Data Science
  • Different Sectors Using Data Science
  • Purpose and Components of Python

Lesson 02 - Data Analytics Overview

  • Data Analytics Process
  • Knowledge Check
  • Exploratory Data Analysis(EDA)
  • EDA-Quantitative Technique
  • EDA - Graphical Technique
  • Data Analytics Conclusion or Predictions
  • Data Analytics Communication
  • Data Types for Plotting
  • Data Types and Plotting
  • Knowledge Check

Lesson 03 - Statistical Analysis and Business Applications

  • Introduction to Statistics
  • Statistical and Non-statistical Analysis
  • Major Categories of Statistics
  • Statistical Analysis Considerations
  • Population and Sample
  • Statistical Analysis Process
  • Data Distribution
  • Dispersion
  • Histogram
  • Testing
  • Correlation and Inferential Statistics

Lesson 04 - Python Environment Setup and Essentials

  • Anaconda
  • Installation of Anaconda Python Distribution (contd.)
  • Data Types with Python
  • Basic Operators and Functions

Lesson 05 - Mathematical Computing with Python (NumPy)

  • Introduction to Numpy
  • Activity-Sequence it Right
  • Demo -Creating and Printing an nd array
  • Class and Attributes of  an array
  • Basic Operations
  • Activity-Slice It
  • Copy and Views
  • Mathematical Functions of Numpy

Lesson 06 - Scientific computing with Python (Scipy)

  • Introduction to SciPy
  • SciPy Sub Package - Integration and Optimization
  • SciPy sub package
  • Demo - Calculate Eigenvalues and Eigenvector
  • SciPy Sub Package - Statistics, Weave and IO

Lesson 07 - Data Manipulation with Pandas

  • Introduction to Pandas
  • Understanding DataFrame
  • View and Select Data Demo
  • Missing Values
  • Data Operations
  • File Read and Write Support
  • Pandas Sql Operation

Lesson 08 - Machine Learning with Scikit–Learn

  • Machine Learning Approach
  • How it Works
  • Supervised Learning Model Considerations
  • Scikit-Learn
  • Pipeline
  • Model Persistence and Evaluation

Lesson 09 - Natural Language Processing with Scikit Learn

  • NLP Overview
  • NLP Applications
  • NLP Libraries-Scikit
  • Extraction Considerations
  • Scikit Learn-Model Training and Grid Search

Lesson 10 - Data Visualization in Python using matplotlib

  • Introduction to Data Visualization
  • Line Properties
  • (x,y) Plot and Subplots

Lesson 11 - Web Scraping with BeautifulSoup

  • Web Scraping and Parsing
  • Understanding and Searching the Tree
  • Navigating options
  • Demo - Navigating a Tree
  • Modifying the Tree
  • Parsing and Printing the Document

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