Course Description

Produced Exclusively for DASCA by John Wiley, USA

Produced exclusively for DASCA by John Wiley, USA under the DASCA Data Science Knowledgeware project. This resource is an integral part of the DASCA certification exam preparation kit provided to all individuals who have formally registered for the DASCA ABDE™ certification program. The courses included in this program are solely for assisting and complementing learning and comprehension on some important topics included in the DASCA certification exam preparation kit provided to learners. The access to these course-modules is restricted to only those individuals who are formally registered in the DASCA ABDE™ certification program.

Course curriculum

  • 1

    Lesson 1

    • 1-1 Anaconda

    • 1-2 Data Types with Python

    • 1-3 Basic Operators and Functions

    • 1-4 Key Takeaways

  • 2

    Lesson 2

    • 2-1 Introduction to Numpy

    • 2-2 Demo 01-creating and Printing an Ndarray

    • 2-3 Basic Operations

    • 2-4 Mathematical Functions of Numpy

    • 2-5 Assignment 01 Demo

    • 2-6 Assignment 02 Demo

    • 2-7 Key Takeaways

  • 3

    Lesson 3

    • 3-1 Introduction to Scipy_2

    • 3-2 Demo 01-creating and Printing an Ndarray_2

    • 3-3 Demo - Calculate Eigenvalues and Eigenvector

    • 3-4 Scipy Sub Package - Statistics, Weave and Io

    • 3-5 Assignment 01 Demo

    • 3-6 Assignment 02 Demo

    • 3-7 Key Takeaways

  • 4

    Lesson 4

    • 4-1 Introduction to Pandas

    • 4-2 Understanding Dataframe

    • 4-3 View and Select Data Demo

    • 4-4 Missing Values

    • 4-5 Data Operations

    • 4-6 File Read and Write Support

    • 4-7 Pandas Sql Operation

    • 4-8 Assignment 01 Demo

    • 4-9 Assignment 02 Demo

    • 4-10 Key Takeaways

  • 5

    Lesson 5

    • 5-1 Machine Learning Approach

    • 5-2 Steps 1 and 2

    • 5-3 How It Works

    • 5-4 Steps 3 and 4

    • 5-5 Supervised Learning Model Considerations

    • 5-6 Scikit-learn

    • 5-7 Supervised Learning Models - Linear Regression

    • 5-8 Supervised Learning Models - Logistic Regression

    • 5-9 Unsupervised Learning Models

    • 5-10 Pipeline_1

    • 5-11 Model Persistence and Evaluation

    • 5-12 Assignment 01

    • 5-13 Assignment 02

    • 5-14 Key Takeaways

  • 6

    Lesson 6

    • 6-1 Introduction to Data Visualization-mp4_1

    • 6-2 (x,y) Plot and Subplots

    • 6-3 Types of Plots

    • 6-4 Assignment 01 Demo

    • 6-5 Assignment 02 Demo

    • 6-6 Key Takeaways

  • 7

    Lesson 7

    • 7-1 Web Scraping and Parsing_1_1

    • 7-2 Navigating a Tree

    • 7-3 Modifying Tree

    • 7-4 Parsing and Printing the Document

    • 7-5 Key Takeaways

  • 8

    Lesson 8

    • 8-1 Why Big Data Solutions Are Provided for Python

    • 8-2 Python Integration with Hdfs Using Hadoop Streaming

    • 8-3 Using Hadoop Streaming for Calculating Word Count_1_1

    • 8-4 Python Integration with Spark Using Pyspark

    • 8-5 Using Pyspark to Determine Word Count

    • 8-6 Assignment 01 Demo

    • 8-7 Assignment 02 Demo

    • 8-8 Key Takeaways