Data Science with Python

Beginner 0(0 Ratings) 13 Students enrolled
Created by Certy Box Last updated Tue, 01-Jun-2021
What will i learn?

Curriculum for this course
94 Lessons 00:00:00 Hours
Data Science Tools
12 Lessons 00:00:00 Hours
  • Data Science Platform 00:00:00
  • Challenges of Deploying Data Science Tools 00:00:00
  • Considerations for Data Science Tools 00:00:00
  • Data Science Workflow 00:00:00
  • Data Science Analytic Tools 00:00:00
  • Data Science Visualization Tools 00:00:00
  • Data Science Database Tools 00:00:00
  • Benefits of Deploying Cloud-Based Tools 00:00:00
  • Challenges of Deploying Cloud-Based Tools 00:00:00
  • What is DevOps 00:00:00
  • DevOps for Data Science 00:00:00
  • Exercise 00:00:00
  • Introduction to Anaconda 00:00:00
  • Introduction to Jupyter/Ipython 00:00:00
  • Working with Jupyter/Ipython 00:00:00
  • Introduction to Numpy 00:00:00
  • Working with Numpy arrays 00:00:00
  • Introduction to Pandas 00:00:00
  • Data Manipulation with Pandas 00:00:00
  • Data Visualisation with Matplotlib 00:00:00
  • Python and Scikit-Learn 00:00:00
  • Supervised Learning with Scikit-Learn 00:00:00
  • Geospatial Analysis using ArcGIS 00:00:00
  • Text analytics with NLTK 00:00:00
  • Social network analysis using Networkx 00:00:00
  • The BeautifulSoup Parser for Python 00:00:00
  • Working with Pyspark for big data 00:00:00
  • Exercise 00:00:00
  • Overview of Distributed Systems 00:00:00
  • Batch vs In-Memory Processing 00:00:00
  • NoSQL Stores 00:00:00
  • Tools for Data Management 00:00:00
  • ETL 00:00:00
  • ETL with Talend Open Studio 00:00:00
  • Data Modeling 00:00:00
  • AI and Machine Learning 00:00:00
  • Data Partitioning 00:00:00
  • Data Reporting 00:00:00
  • Exercise 00:00:00
  • Introduction to NumPy & NumPy Ecosystem 00:00:00
  • Array Creation 00:00:00
  • Printing Arrays 00:00:00
  • Basic Array Operations 00:00:00
  • Universal Functions 00:00:00
  • Indexing & Slicing 00:00:00
  • Iterating over arrays 00:00:00
  • Reshaping Arrays 00:00:00
  • Work with DataFrames 00:00:00
  • Exercise 00:00:00
  • Splitting NumPy Arrays 00:00:00
  • Images as Arrays 00:00:00
  • Image Manipulation Using Numpy 00:00:00
  • Views & NumPy Arrays 00:00:00
  • Introduction to Index Masks 00:00:00
  • Applying index masks 00:00:00
  • Indexing with Boolean Masks 00:00:00
  • Structured Arrays 00:00:00
  • understanding array broadcasting 00:00:00
  • Applying broadcasting rules on array operations 00:00:00
  • Exercise 00:00:00
  • Iterating Over the Contents of a DataFrame 00:00:00
  • Exporting a DataFrame 00:00:00
  • Sorting 00:00:00
  • Handling Missing Data 00:00:00
  • Grouping with a Multi-Index 00:00:00
  • Merging Dataframes 00:00:00
  • applying Join operations on dataframes 00:00:00
  • Pandas and Relational Databases 00:00:00
  • Exercise 00:00:00
  • Features of Pandas and its ecosystem 00:00:00
  • Working with Pandas 00:00:00
  • Introduction to Dataframes 00:00:00
  • Add & Delete DataFrame Contents 00:00:00
  • Select parts of a dataframe 00:00:00
  • Access pandas dataframes 00:00:00
  • Introduction to multi-indexing in a dataframe 00:00:00
  • Reshape DataFrames 00:00:00
  • Reshape dataframes using stack & melt operations 00:00:00
  • Exercise 00:00:00
  • Machine Learning Concepts 00:00:00
  • Machine Learning and Deep Learning 00:00:00
  • Machine Learning and AI Correlation 00:00:00
  • Installing Python for Machine Learning 00:00:00
  • Supervised Learning Algorithm 00:00:00
  • Analytics Types and Techniques 00:00:00
  • Introduction to Seaborn 00:00:00
  • Simple Univariate Distributions 00:00:00
  • Simple Bivariate Distributions 00:00:00
  • Configure Univariate Distribution Plots 00:00:00
  • Explore Different Types of Bivariate Distributions 00:00:00
  • Analyze Multiple Variable Pairs 00:00:00
  • Regression Plots 00:00:00
  • Themes and Styles in Seaborn 00:00:00
  • Exercise 00:00:00
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