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Alteryx: Data Science for Non-Scientists

Designed specifically for beginners with no background in Data Science, Computer Science or Alteryx

  1. Topics
  2. IT & Software
  3. Alteryx Designer

Alteryx: Data Science for Non-Scientists

InstructorJed Guinto
Duration5h 14m
Students15.3K
Rating4.5 (225)
Sponsored
Price
$14.99
Coupon
None
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Comidoc Analysis

Alteryx ETL and Data Preparation via Core Toolsets

Strengths

Core ETL Toolset

Covers essential data preparation including file ingestion, filtering, summarizing, and formula applications.

Practical Application

Includes a case study focused on stock market and portfolio analysis to apply tool workflows.

Limitations

Missing Machine Learning

One sampled review suggests that despite the title and description, the active curriculum lacks the machine learning and predictive modeling content expected by some learners.

Strictly Beginner Level

The depth of instruction is geared toward those with no prior experience, which may feel too basic for more advanced users.

Best suited to

  • Beginners seeking to automate data cleansing
  • Users transitioning from Excel-sited workflows

Less suited to

  • Learners expecting predictive modeling or machine learning
  • Users looking for advanced statistical depth

Comidoc Score

5.9/10

Worth considering
Beginner-friendly

Comidoc verdict

The learning path centers on Alteryx Designer fundamentals, specifically focusing on data ingestion and transformation. Learners progress through essential toolsets such as filtering, sorting, and joining various data types to prepare them for automated workflows.

The primary strength lies in the clarity of instruction and the inclusion of practical case studies. However, a significant gap exists between the course's marketing claims regarding machine learning and the actual technical depth provided.

Editorial course preview

What the public course preview actually shows

These 4 complementary views highlight concrete, legible examples from the course presentation.

Preview 1 of 4

This slide outlines the course structure in two stages, identifying Data Cleansing and Preparation followed by Machine Learning as the key components of the curriculum.

Preview 2 of 4

This slide outlines the beginner-level curriculum, covering essential data manipulation techniques such as inputs, outputs, sorting, filtering, and joins.

Preview 3 of 4

This slide outlines the intermediate curriculum, covering essential data preparation techniques such as filtering, formulas, joins, and spatial analytics.

Preview 4 of 4

This course slide outlines the Machine Learning and A.I. section, covering data preparation, regression models, decision trees, and time series analysis.

Selected from the course's public promotional preview. These images document visible presentation material only; they do not represent the complete paid curriculum.

This course is best suited for absolute beginners who want to master data cleansing and ETL processes using Alteryx.

Score breakdown

Curriculum depth
5.8

The curriculum covers essential ETL tools but lacks the machine learning depth advertised in the description.

Applied learning
6.5

Instruction includes a specific case study and lab resources for practical application.

Clarity & experience
6.5

Learner signals indicate the instruction is well-explained and easy to follow.

Currency & reliability
5.0

The available evidence does not establish enough about current reliability to move this dimension away from neutral.

Audience fit
5.0

Alteryx fundamentals and data cleansing workflows are prioritized over the promised machine learning instruction.

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