Data Science Essentials Training
Data Science Essentials Training
Order this unique E-Learning Data Science Essentials course Training online, 1 year of 24/7 access to rich interactive videos, progress through reporting and testing.
Read more- Brand:
- Data Science
- Discounts:
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- Buy 2 for €244,02 each and save 2%
- Buy 3 for €241,53 each and save 3%
- Buy 4 for €239,04 each and save 4%
- Buy 5 for €236,55 each and save 5%
- Buy 10 for €224,10 each and save 10%
- Buy 25 for €211,65 each and save 15%
- Buy 50 for €199,20 each and save 20%
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- Award Winning E-learning
- Lowest price guarantee
- Personalized service by our expert team
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Data Science Essentials E-Learning
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
| Language | English |
|---|---|
| Qualifications of the Instructor | Certified |
| Course Format and Length | Teaching videos with subtitles, interactive elements and assignments and tests |
| Lesson duration | 9:49 Hours |
| Progress monitoring | Yes |
| Access to Material | 365 days |
| Technical Requirements | Computer or mobile device, Stable internet connections Web browsersuch as Chrome, Firefox, Safari or Edge. |
| Support or Assistance | Helpdesk and online knowledge base 24/7 |
| Certification | Certificate of participation in PDF format |
| Price and costs | Course price at no extra cost |
| Cancellation policy and money-back guarantee | We assess this on a case-by-case basis |
| Award Winning E-learning | Yes |
| Tip! | Provide a quiet learning environment, time and motivation, audio equipment such as headphones or speakers for audio, account information such as login details to access the e-learning platform. |
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