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Home » Course » Data Science- Level 2- Canadian Arab Instructor

Data Science- Level 2- Canadian Arab Instructor

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Data Science COURSE
Current Status
Not Enrolled
Price
$899
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Course Title: Data Science- Level 2

Course Status – Accepting applications (limited seats)

Broad Aims Of This Course

This course is built on a project-based learning model, which will allow participants to use data analysis, modelling, Python programming, and more to solve real business analytical problems.

In this course you will learn:

  • Programming for Data Science
  • Cleaning and Analysing Data
  • Visualizations of data
  • Data Modelling

Click the +/- (accordion) symbol below to display relevant details in collapsible content format

Course Structure

This course has a total duration of 30 hours of LIVE Virtual Classroom Training:

LevelTotal weeksHours per weekDaysTimings
Intermediate to Advanced103Sundays6:30- 9:30 PM
UAE time (Dubai)

*You will require a data/ internet speed of 5 Mbps to access the LIVE Virtual Class with best results for video and audio interaction. Check your internet speed here (https://fast.com/)

**Participants can access the class by logging into their accounts at https://careerz4me.com/ using either a laptop or desktop only.

Language of Instruction
  • The language of instruction for this course is English.
  • The Teacher is fluent in English and Arabic
  • The Teacher will communicate with students in English only and all activities including assessments will be conducted in English.
Pre- requisites

You will need a laptop (preferable Windows) to install Anaconda so we can work with Python and Jupyter notebooks

Learning Outcomes
On the completion of this course, participants will be able to do:
Intro to Data Science
  • What is Data Science?
  • Python + Anaconda
Data Structures
  • Lists
  • Dictionaries
  • Pandas
Working with Data
  • Querying Data
  • Combining Data
  • Time-Series Data
Data Visualization
  • Matplotlib
  • Bokeh
  • Using Model
  • Visualizations
Data Cleaning
  • Cleaning Data
  • Missing Data
Statistics/Math
  • Statistics
  • Vectors and Matrices
  • Linear Regression
Numerical Modelling
  • Linear Regression Models
  • Polynomial Regression models
  • Overfitting
  • Spline Interpolation
Classification
  • Logistic Regression Models
  • Naïve Bayes
  • Decision Trees
Model Validation
  • Distribution Fitting
  • Testing goodness of fit
  • Cross validations
Future paths
  • Other modelling techniques
  • Optimization
  • Random forests
Methodology

Different learning material will be used:

  • Live Classroom Training
  • Practice worksheets
Final Assessment & Certificate
  • Final assessment will be in the last session of the course.
  • ‘Course Completion Certificate’ will be sent to students within 2 weeks of successful completion of the course.
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Previous Data Analytics (Level 1- Microsoft Excel, MySQL and Tableau)- Canadian Arab Instructor Next EASA Part 66 Cat A1 B1 BASIC EXAMS – DUBAI, UNITED ARAB EMIRATES
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