Course curriculum

    1. Welcome!

    2. 👤 AstroLabs Chat

    3. Zoom Link

    4. Discussion Boards (Support)

    1. Introduction to using data in 2021

    2. Why choose Python (differences between Python and R)

    3. Installing Visual Studio Code

    4. Python for Data Engineering

    5. How Machine Learning & Deep Learning Work

    6. Understanding Predictive Analytics and Prescriptive Analytics

    7. Overview of Scraping Data and Creating Data

    1. Definition of Algorithms Definition of Data Structures

    2. Blocks, Scope & Conditionals

    3. Variables and Data Types

    4. Dictionaries

    5. Algorithm Practice

    6. Basics of Data Science to Solve Problems

    1. Tools for Data Science, Applications for Data Analysis and Languages for Data Ccience

    2. Selecting Optimal Data Graphics, Communicating with Color and C Analyses for Data Science

    3. Clustering, Classifying and Anomaly Detection

    4. Data Preparation Basics Filtering and Selecting

    5. Grouping and Aggregation & Conditional Statements

    1. The Data Collection Process

    2. Practical Data Science Applications: Getting Data in Using Web Scraping

    3. Mocking Inputs / Pagination - Search and Filters

    4. Saving, Reading / Writing to a File

    5. Data Sourcing via Web Scraping

    6. Data Parsing

    7. Cleaning and Stemming Textual Data

    8. Project- Scraping Yellow Pages

    1. Descriptive Analyses and Predictive Models

    2. Anomaly Detection, Dimensionality Reduction, Feature Selection and Creation

    3. Mathematics for Data Science: Algebra & Calculus

    4. Acting on Data Science, Interpretability Actionable Insights

    5. Collaborative Analytics with Plotly

    6. Opening Files Text vs. Binary Mode

    7. Practical Data Visualization

About this course

  • 63 lessons