Data Science with Python Overview

Python course provide trainees with an in-depth of the basic and advanced concepts of Python like writing Python scripts, sequence and file operations in Python. This training teaches learners to use libraries like pandas, numpy, matplotlib, scikit. This course help trainees in mastering different concepts like Python machine learning, sequence and scripts. 

Data Science with Python Key Features

100% Money Back Guarantee
  • Live Training 68 hours of blended learning
  • Live Training 24 hours of online self-paced training
  • Live Training 44 hours of instructor-led training
  • Live Training 4 industry-based projects
  • Live Training Interactive learning with jupyter notebooks integrated labs
  • Live Training Dedicated mentoring sessions
  • Live Training No Exam Included

Skills Covered

  • Mathematical computing
  • Data wrangling
  • Data visualization
  • Data exploration

Benefits

  • High demand in the market
  • Better career prospects
  • Lucrative pay packages 

Training Package Options

Self-paced Learning

23000.00

    • Lifetime access to high-quality self-paced eLearning content curated by industry experts
    • 4 hands-on projects to perfect the skills learnt
    • 3 simulation test papers for self-assessment
    • Lab access to practice live during sessions
    • 24x7 learner assistance and support

Live Virtual Class

25000.00

    • Everything in Self-Paced Learning, plus
    • 90 days of flexible access to online classes
    • Live, online classroom training by top instructors and practitioners

                         

                   

  • Classes starting from:-
10 Jun 22
06 Jun 22
Show all classes

Course Content

  • Data Science with Python

    • Lesson 00-Course Overview

        • Course Overview
        •  Accessing Practice Lab
    • Lesson 01- Data Science Overview

        • Introduction to Data Science
        •  Different Sectors Using Data Science
        •  Purpose and Components of Python
        •  Quiz
        •  Key Takeaways
    • 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
        • 2.007 Data Analytics Communication
        •  Data Types for Plotting
        • 2.009 Data Types and Plotting
        •  Quiz
        • Key Takeaways
        • 2.10 Knowledge Check
    • Lesson 03 - Statistical Analysis and Business Application

        • Introduction to Statistics
        • Statistical and Non-statistical Analysis
        • Major Categories of Statistics
        • Statistical Analysis Considerations
        • Population and Sample
        • Statistical Analysis Process
        •  Data Distribution
        •  Dispersion
        •  Knowledge Check
        • Histogram
        • Knowledge Check
        •  Testing
        • Knowledge Check
        •  Correlation and Inferential Statistics
        •  Quiz
        • Key Takeaways
    • Lesson 04 - Python Environment Setup and essential

        • Anaconda
        • Installation of Anaconda Python Distribution (contd.)
        •  Data Types with Python
        • Basic Operators and Functions
        •  Quiz
        • Key Takeaways
    • Lesson 05 - Mathematical Computing with Python (NumPy)

        • Introduction to Numpy
        • Activity-Sequence it Right
        • Demo 01-Creating and Printing an ndarray
        • Knowledge Check
        •  Class and Attributes of ndarray
        •  Basic Operations
        • Activity-Slice It
        •  Copy and Views
        • Mathematical Functions of Numpy
        •  Analyse GDP of Countries
        •  Assignment 01 Demo
        • Analyse London Olympics Dataset
        •  Assignment 02 Demo
        •  Quiz
        • Key Takeaways
    • Lesson 06 - Scientific Computing with Python ( Scipy)

        • Introduction to SciPy
        • SciPy Sub Package - Integration and Optimization
        •  Knowledge Check
        •  SciPy sub package
        • Demo - Calculate Eigenvalues and Eigenvector
        • Knowledge Check
        •  SciPy Sub Package - Statistics, Weave and IO
        •  Solving Linear Algebra problem using SciPy
        • Assignment 01 Demo
        •  Perform CDF and PDF using Scipy
        •  Assignment 02 Demo 
        •  Quiz
        • Key Takeaways
    • Lesson 07 - Data Manipulation with Pandas

        •  Introduction to Pandas
        •  Knowledge Check
        • Understanding DataFrame
        •  View and Select Data Demo
        • Missing Values
        •  Data Operations
        •  Knowledge Check
        • File Read and Write Support
        • Knowledge Check-Sequence it Right
        •  Pandas Sql Operation
        • Analyse the Federal Aviation Authority Dataset using Pandas
        • Assignment 01 Demo
        •  Analyse NewYork city fire department Dataset
        •  Assignment 02 Demo
        •  Quiz
        • Key Takeaways
    • Lesson 08 - Machine Learning with SciKit- Learn

        • Machine Learning Approach
        • Steps One and Two
        • Steps Three and Four
        •  How it Works
        •  Steps Five and Six
        •  Supervised Learning Model Consideration
        •  ScikitLearn
        • Knowledge Check
        • Supervised Learning Models - Linear Regression
        • Supervised Learning Models - Logistic Regression
        •  Unsupervised Learning Models
        • Pipeline
        •  Model Persistence and Evaluation
        •  Knowledge Check
        •  Analysing Ad Budgets for different media channels
        •  Assignment One
        •  Building a model to predict Diabetes
        •  Assignment Two
        • Knowledge Check
        •  Key Takeaways
    • Lesson 09 - Natural Language Processing With SciKit Learn

        •  NLP Overview
        •  Scikit Learn-Model Training and Grid Search
        • Analysing Spam Collection Data
        •  Demo Assignment 01
        •  Sentiment Analysis using NLP
        • Demo Assignment 02
        •  Quiz
        • Key Takeaways
    • Lesson 10 - Data Visualization in Python Using Matplotlib

        • Introduction to Data Visualization
        •  Knowledge Check
        •  Line Properties
        •  (x,y) Plot and Subplots
        •  Knowledge Check
        •  Types of Plots
        •  Draw a pair plot using seaborn library
        •  Assignment 01 Demo
        •  Analysing Cause of Death
        •  Assignment 02 Demo
        •  Quiz
        •  Key Takeaways
    • Lesson 11 - Web Scraping with BeautifulSoup

        • Web Scraping and Parsing
        • Knowledge Check
        •  Understanding and Searching the Tree
        • Navigating options
        •  Demo3 Navigating a Tree
        • Knowledge Check
        • Modifying the Tree
        •  Parsing and Printing the Document
        •  Web Scraping of Simplilearn Website
        • Assignment 01 Demo
        •  Web Scraping of Simplilearn Website Resource page
        • Assignment 02 demo
        •  Quiz
    • Lesson 12 - Python Integration with Hadoop MapReduce and Spark

          • Why Big Data Solutions are Provided for Python
          •  Hadoop Core Components
          •  Python Integration with HDFS using Hadoop Streaming
          •  Demo 01 - Using Hadoop Streaming for Calculating Word Count
          •  Knowledge Check
          •  Python Integration with Spark using PySpark
          •  Demo 02 - Using PySpark to Determine Word Count
          •  Knowledge Check
          •  Determine the wordcount
          • Assignment 01 Demo
          •  Display all the airports based in New York using PySpark
          •  Assignment 02 Demo
          •  Quiz
          •  Key takeaways