Certified Professional in Data Science - Practice Test

Validate Your Skills in Statistics, Python, Machine Learning, and Data Analysis for Job Interviews

IMPORTANT: This course contains Practice Tests only. It does not contain video tutorials. These tests are designed to assess your Data Science knowledge and prepare you for technical interviews.

Data Science is the "Best Job of the 21st Century." But the interview process is brutal.

Companies don't just want someone who can import a library. They want someone who understands the math behind the models, knows how to clean messy data, and can derive actionable insights from complex datasets.

Do you know the difference between Supervised and Unsupervised learning? Can you confidently explain a P-Value? Do you know how to handle missing data in Pandas?

Welcome to the Ultimate Data Science Knowledge Check.

This course is designed to bridge the gap between "watching tutorials" and "being job ready." We test your ability to think like a Data Scientist.

What to expect in this course:
This course consists of 2 Full Length Practice Tests covering the full data pipeline.

• Foundations of Data Analysis. (Statistics, Probability, Excel Analysis and Data Visualization).

• Python & Machine Learning. (Python Syntax, Pandas/NumPy, Algorithms, Model Evaluation and Data Cleaning).

  
  

Topics covered in these questions:

• Statistics & Probability: Mean/Median/Mode, Standard Deviation, Hypothesis Testing and Distributions.

• Python for Data Science: Manipulating data frames with Pandas, numerical analysis with NumPy, and visualization with Matplotlib/Seaborn.

• Machine Learning Concepts: Regression vs Classification, Clustering, Overfitting/Underfitting and Bias Variance Tradeoff.

• Data Cleaning: Handling missing values, outliers and feature scaling.

• Excel for Analysts: Pivot Tables, VLOOKUP and conditional logic.

  
  

Why take these Practice Tests?

1. Interview Preparation: These questions are modeled after real technical screening questions from top tech companies.

2. Validate Your Toolkit: Ensure you aren't just memorizing code, but understanding the concepts of Data Science.

3. Detailed Explanations: We explain WHY an answer is correct. For example, we don't just say "Use Mean Imputation"; we explain when to use Mean Imputation vs Dropping rows.

   
   

Who is this course for?

• Aspiring Data Scientists preparing for their first role.

• Data Analysts looking to move into Machine Learning.

• Students wanting to test their Python and Statistics knowledge.

  
  

What does this course offer you?

• 2 Comprehensive Practice Tests: 40+ Questions (Timed at 30 minutes each).

• Multi-Disciplinary Approach: Covers Math, Coding, and Business Logic.

• Instant Feedback: See exactly where your gaps are (e.g: "Strong in Python, Weak in Statistics").

• Lifetime Access: Retake as many times as you need.

  
  

Don't rely on guesswork
Data Science is a precision field. Enroll today, test your skills, and prove you are a Certified Professional in Data Science.