Data Science Training

by MindTech Montreal Claim Listing

The Data Science training allows you to implement the methods and tools intended to interpret the data.

Price : Enquire Now

Contact the Institutes

Fill this form

Advertisement

MindTech Montreal Logo

img Duration

Please Enquire

Course Details

The Data Science training allows you to implement the methods and tools intended to interpret the data.


Pedagogical objectives of the Data Science Training:

  • Use R to clean/analyze and visualize data
  • Navigate the entire data science pipeline from data acquisition to publication
  • Use GitHub to manage data science projects
  • Perform regression/least squares analyzes and inferences using regression models

 

Data Science Training Course:

  • Module 1 of the Data Science training: The tools of the data scientist
    • Set up R, R-Studio, Github and other useful tools
    • Explain the essential concepts of study design
    • Understand data, issues and tools used by data analysts
    • Create a Github repository
  • Module 2 of the Data Science training: Programming in R
    • The essential concepts of the programming language
    • R loop functions and debugging tools
    • Configure statistical programming software
    • Gather detailed information using the R profiler
  • Module 3 of the Data Science training: Obtaining and sorting data
    • Understand common data storage systems
    • Use R for text and date manipulation
    • Apply basic principles of data cleansing to make data/clean.
    • Obtain usable data from the web, APIs and databases
  • Module 4 of the Data Science training: Analytical exploration of data
    • Understand analytical graphs and the basic plotting system in R
    • Realize very high-dimensional graphical representations of data
    • Use advanced graphics systems such as the Lattice system
    • Apply cluster analysis techniques to locate patterns in data
  • Module 5 of the Data Science course: Reproducible research
    • Organize data analysis to make it more reproducible
    • Determine the reproducibility of the analysis project
    • Write a reproducible data analysis using knitting
    • Publish reproducible web documents using the Markdown feature
  • Module 6 of the Data Science training: Statistical inference
    • Understand the process of drawing conclusions about populations or scientific truths from data
    • Describe variability, distributions, limits and confidence intervals
    • Use p-values, confidence intervals and permutation tests
    • Make informed data analysis decisions
  • Data Science Training Module 7: Regression Models
    • Use regression analysis, least squares, and inference
    • Understand model cases of ANOVA and ANCOVA
    • Review residuals and variability analysis
    • Describe new uses for regression models such as scatterplot smoothing
  • Module 8 of the Data Science training: Practical mechanical learning
    • Use the basics of constructing and applying prediction functions
    • Understand concepts such as training and testing sets, over-equipment, and error rates
    • Describe machine learning methods such as regression or classification trees
    • Explain the full process of constructing prediction functions
  • Module 9 of the Data Science course: Development of data products
    • Develop basic applications and interactive graphics using GoogleVis
    • Use the flyer to create annotated interactive maps
    • Build an R Markdown presentation that includes a data visualization
    • Create a data product that tells a story to a mass audience
  • Data Science Training Module 10: Final Data Science Project
    • Create a useful data product for the public
    • Apply your exploratory data analysis skills
    • Build an efficient and accurate prediction model
    • Create a presentation folder to showcase your results
  • Montreal Branch

    442 Rue Saint-Gabriel QC H2Y 2Z9, Montreal

Check out more Data Science courses in USA

Training Ottawa Logo

Microsoft Power BI

This two-day course provides students with the knowledge and skills to analyze data with Power BI.

by Training Ottawa [Claim Listing ]
NAD School Logo

Intro To CGI In Artificial Intelligence (Bespoke Learning)

Discovering Artificial Intelligence (AI) within Computer Generated Imaging (CGI). Understanding the theoretical aspects and the ongoing research. Integrating AI into daily creative work, visual creations, architecture, design and art. Exploring the AI ??universe.

by NAD School [Claim Listing ]
Training Vancouver Logo

Microsoft Power BI

This two-day course provides students with the knowledge and skills to analyze data with Power BI. Prerequisites: Basic knowledge of the Microsoft Windows operating system and its core functionality; Familiarity with Microsoft Office applications – particularly Excel.

by Training Vancouver [Claim Listing ]
Stem Minds Logo

AI Art (Artificial Intelligence)

Artificial Intelligence has continued to become more and more sophisticated from social media to search engines to auto correct, we have made a lot of progress in behaviour prediction.

by Stem Minds [Claim Listing ]
New Horizons London Logo

Using Data Science Tools in Python (v1.0)

This course is designed for experienced programmers and those with a solid working knowledge of computing technology looking to gain the skills needed to successfully use these key libraries to extract useful insights from data, and as a result, provide great value to the business.

by New Horizons London [Claim Listing ]

© 2025 coursetakers.com All Rights Reserved. Terms and Conditions of use | Privacy Policy