Data Science Essentials

Data Science Essentials

Order this unique E-Learning course Data Science Essentials online, 1 year 24/7 access to rich interactive videos, speech, progress monitoring through reports and tests per chapter to test the knowledge directly.

Data science is an applied study of data for statistical analysis and problem solving. This path of courses covers the data science pipeline needed by the everyday data scientist: data wrangling, analysis, machine learning, and communication and visualization.

Course content

Defining Data Science

Course: 19 Minutes

• Course Introduction
• What is Data Science?
• What is Data Wrangling?
• What is Big Data?
• What is Machine Learning?

Implementing Data Science

Course: 21 Minutes

• Data Science Terminology
• Data Communication
• Data Science Pipeline
• Data Science Tools

Practice: Exploring Data Science

Course: 4 Minutes

• Exercise: Explore Your Data Science Needs

Data Extraction

Course: 31 Minutes

• Course Introduction
• Basic Data Gathering
• Gathering Web Data
• Extracting Spreadsheet Data with in2csv
• Extracting Spreadsheet Data with Agate
• Extracting Legacy Data from dBASE Tables
• Extracting HTML Data

Metadata

Course: 24 Minutes

• Gathering Metadata
• Working with HTTP Headers
• Working with Linux Log Files
• Working with Email Headers

Remote Data

Course: 15 Minutes

• Connecting to Remote Data
• Copying Remote Data
• Synchronizing Remote Data

Practice: Curl and HTML

Course: 4 Minutes

• Exercise: Explore HTML Tables

Introduction to Data Filtering

Course: 59 Minutes

• Course Overview
• Data Filtering Techniques and Tools
• Processing Date Formats
• Filtering HTTP Headers
• Filtering CSV Data
• Replacing Values with sed
• Dropping Duplicate Data
• Working with JPEG Headers
• Filtering PDF Files
• Filtering for Invalid Data
• Parsing robots.txt

Practice: Filtering Dates

Course: 3 Minutes

• Exercise: Cull Old Data

File Format Conversions

Course: 23 Minutes

• Course Introduction
• Converting CSV to JSON
• Converting XML to JSON
• Converting CSV to SQL
• Converting SQL to CSV
• Changing CSV Delimiters

Data Conversions

Course: 13 Minutes

• Converting Dates
• Converting Numbers
• Rounding Numbers

Optical Character Recognition

Course: 11 Minutes

• OCR JPEG Images
• Extracting Text from PDF Files

Practice: Converting Dates

Course: 2 Minutes

• Exercise: Convert Dates to ISO 8601

Introduction to Data Exploration

Course: 53 Minutes

• Course Introduction
• Exploring CSV Data
• Exploring CSV Statistics
• Querying CSV Data
• Plotting from the Command Line
• Counting Words
• Exploring Directory Trees
• Determining Word Frequencies
• Taking Random Samples
• Finding the Top Rows
• Finding Repeated Records
• Identifying Outliers in Data

Practice: Exploring Word Frequencies

Course: 4 Minutes

• Exercise: Count Word Frequencies in a Classic Book

Introduction to Data Integration

Course: 41 Minutes

• Course Overview
• Joining CSV Data
• Concatenating Log Files
• Sorting Text Files
• Merging XML Data
• Aggregating Data
• Normalizing Data
• Denormalizing Data
• Pivoting Data Tables
• Homogenizing Rows

Practice: Joining CSV Data

Course: 2 Minutes

• Exercise: Merge Two CSV Documents into One

Data Science Math

Course: 24 Minutes

• Course Introduction
• Basic Data Science Math
• Linear Algebra Vector Math
• Linear Algebra Matrix Math
• Linear Algebra Matrix Decomposition

Data Analysis Concepts

Course: 39 Minutes

• Data Formation
• Introduction to Probability
• Working with Events
• Working with Probabilit
• Continuous Probability Distributions
• Discrete Probability Distributions
• Introduction to Bayes Theorem

Estimates and Measures

Course: 36 Minutes

• Sampling Data
• Statistical Measures
• Estimators
• Sampling Distributions
• Confidence Intervals
• Hypothesis Tests
• Chi-Square

Practice: Identifying Data

Course: 2 Minutes

• Exercise: Identify Data Sets by Type

Machine Learning Introduction

Course: 24 Minutes

• Course Introduction
• Introduction to Supervised Learning
• Introduction to Unsupervised Learning
• Understanding Linear Regression
• Working with Predictors

Regression and Classification

Course: 19 Minutes

• Understanding Logistic Regression
• Understanding Dummy Variables
• Using Naive Bayes Classification
• Working with Decision Trees

Clustering

Course: 14 Minutes

• K-means Clustering
• Using Cluster Validation
• Using Principal Component Analysis

Errors and Validation

Course: 20 Minutes

• Introduction to Errors
• Defining Underfitting
• Defining Overfitting
• Using K-folds Cross Validation
• Using Neural Networks
• Support Vector Machines (SVM)

Practice: Choosing a Method

Course: 2 Minutes

• Exercise: Choose a Machine Learning Method

Introduction to Data Communication

Course: 32 Minutes

• Course Introduction
• Effective Communication and Visualization
• Correlation Versus Causation
• Simpson's Paradox
• Presenting Data
• Documenting Data Science
• Visual Data Exploration

Plotting

Course: 45 Minutes

• Creating Scatter Plots
• Plotting Line Graphs
• Creating Bar Charts
• Creating Histograms
• Creating Box Plots
• Creating Network Visualizations
• Creating a Bubble Plot
• Creating Interactive Plots

Practice: Creating a Scatter Plot

Course: 3 Minutes

• Exercise: Create a Scatter Plot

Specificaties

Taal: Engels
Kwalificaties van de Instructeur: Gecertificeerd
Cursusformaat en Lengte: Lesvideo's met ondertiteling, interactieve elementen en opdrachten en testen
Lesduur: 9:49 uur
Voortgangsbewaking: Ja
Toegang tot Materiaal: 365 dagen
Technische Vereisten: Computer of mobiel apparaat, Stabiele internetverbindingen Webbrowserzoals Chrome, Firefox, Safari of Edge.
Support of Ondersteuning: Helpdesk en online kennisbank 24/7
Certificering: Certificaat van deelname in PDF formaat
Prijs en Kosten: Cursusprijs zonder extra kosten
Annuleringsbeleid en Geld-Terug-Garantie: Wij beoordelen dit per situatie
Award Winning E-learning: Ja

Tip! Zorg voor een rustige leeromgeving, tijd en motivatie, audioapparatuur zoals een koptelefoon of luidsprekers voor audio, accountinformatie zoals inloggegevens voor toegang tot het e-learning platform.