Python Statistics for Data Science Course Certification Training

Python Statistics for Data Science Certification Training in Monterrey, Mexico

Comprehensive Understanding: The course aims to provide a complete grasp of statistical analysis.
Practical Application: It focuses on how to perform statistical analysis and make data-driven decisions.
Interactive Learning: The course uses interactive lessons and hands-on exercises for a practical learning experience.
Key Skills Taught: It covers specific techniques like hypothesis testing and regression analysis.
Target Audience: The course is designed for anyone who wants to enhance their data science skills and gain a deeper understanding of statistics.
Career Focus: It is intended to provide knowledge to succeed in the field of data science.

Python Statistics for Data Science Course Overview

Python Scripting allows programmers to build applications easily and rapidly. This course is an introduction to Python scripting, which focuses on the concepts of Python, it will help you to perform operations on variable types using Pycharm. You will learn the importance of Python in real time environment and will be able to develop applications based on Object Oriented Programming concept. At the end of this course, you will be able to develop networking applications with suitable GUI.

In this course you will:

Be introduced to data and its types and accordingly sample data and derive meaningful information from the data in terms different statistical parameters.
Learn about probability, interpret & solve real-life problems using probability. You will get to know the power of probability with Bayesian Inference.
Draw inferences from present data and construct predictive models using different inferential parameters (as a constraint).
Learn the different methods of testing the alternative hypothesis.
Get an introduction to Clustering as part of this Module which forms the basis for machine learning.
Learn the roots of Regression Modelling using statistics.

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Python Statistics for Data Science Course Topics

Goal: In this module, you will be introduced to data and its types and accordingly sample data and derive meaningful information from the data in terms different statistical parameters.

Objectives: At the end of this Module, you should be able to:

Understand various data types
Learn Various variable types
List the uses of variable types
Explain Population and Sample
Discuss sampling techniques
Understand Data representation

Topics:

Introduction to Data Types
Numerical parameters to represent data
Mean
Mode
Median
Sensitivity
Information Gain
Entropy
Statistical parameters to represent data

Hands-On/Demo

Estimating mean, median and mode using python
Calculating Information Gain and Entropy

Goal: In this module, you should learn about probability, interpret & solve real-life problems using probability. You will get to know the power of probability with Bayesian Inference.

Objectives: At the end of this Module, you should be able to:
Understand rules of probability
Learn about dependent and independent events
Implement conditional, marginal and joint probability using Bayes Theorem
Discuss probability distribution
Explain Central Limit Theorem

Topics:
Uses of probability
Need of probability
Bayesian Inference
Density Concepts
Normal Distribution Curve

Hands-On/Demo:
Calculating probability using python
Conditional, Joint and Marginal Probability using Python
Plotting a Normal distribution curve

Goal: Draw inferences from present data and construct predictive models using different inferential parameters (as a constraint).

Objectives: At the end of this Module, you should be able to:

Understand the concept of point estimation using confidence margin
Draw meaningful inferences using margin of error
Explore hypothesis testing and its different levels

Topics:

Point Estimation
Confidence Margin
Hypothesis Testing
Levels of Hypothesis Testing

Hands-On/Demo:

Calculating and generalizing point estimates using python
Estimation of Confidence Intervals and Margin of Error

Goal: In this module, you should learn the different methods of testing the alternative hypothesis.

Objectives: At the end of this module, you should be able to:

Understand Parametric and Non-parametric Testing
Learn various types of parametric testing
Discuss experimental designing
Explain a/b testing

Topics:

Parametric Test
Parametric Test Types
Non- Parametric Test
Experimental Designing
A/B testing

Hands-On/Demo:

Perform p test and t tests in python
A/B testing in python

Goal: Get an introduction to Clustering as part of this Module which forms the basis for machine learning.

Objectives: At the end of this module, you should be able to:

Understand the concept of association and dependence
Explain causation and correlation
Learn the concept of covariance
Discuss Simpson’s paradox
Illustrate Clustering Techniques

Topics:

Association and Dependence
Causation and Correlation
Covariance
Simpson’s Paradox
Clustering Techniques

Hands-On/Demo:

Correlation and Covariance in python
Hierarchical clustering in python
K means clustering in python

Goal: Learn the roots of Regression Modelling using statistics.

Objectives: At the end of this module, you should be able to:

Understand the concept of Linear Regression
Explain Logistic Regression
Implement WOE
Differentiate between heteroscedasticity and homoscedasticity
Learn the concept of residual analysis

Topics:

Logistic and Regression Techniques
Problem of Collinearity
WOE and IV
Residual Analysis
Heteroscedasticity
Homoscedasticity

Hands-On/Demo:

Perform Linear and Logistic Regression in python
Analyze the residuals using python

Why choose our Python Statistics for Data Science in Monterrey, Mexico?

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Python Statistics for Data Science Frequently Asked Questions

Yes, we do offer additional discounts to group and corporate training customers. Please email us at [email protected] to find out more about our group discount offerings.

Use the "Submit your query"section in this page or check "Contact Us" section. Alternatively, please send an email to [email protected] to find out more about our course offerings.

If you're unemployed right now, or you're a student taking this course for career growth, we do provide additional discounts for you on selected courses. Please email [email protected] to avail this benefit and discount coupon.

Note: These discounts are available on selected courses only.

We do not offer placement or placement assistance services at this time. However, our training is designed to equip you with in-demand skills, hands-on experience, and certification readiness to help you confidently pursue new career opportunities. Many of our learners have successfully transitioned into new roles or advanced in their careers based on the knowledge and certifications gained through our programs

Python Statistics for Data Science Certification Training in Monterrey, Mexico

✅ Monterrey, Mexico – Advance Your Career in a Leading Industrial and Technology Hub

Monterrey, one of Mexico’s largest and most industrialized cities, is a major center for manufacturing, technology, and research-driven enterprises. Anchored by multinational corporations, advanced manufacturing plants, and innovation-focused institutions, the city offers strong career opportunities for professionals with technical expertise and project management skills.

Certifications in DevOps, Cloud Computing, Project Management, and Quality Management make you a highly sought-after candidate for organizations managing complex, high-stakes operations. At the same time, skills in AI, Data Science, and Business Intelligence are increasingly valuable as local industries embrace digital transformation and data-driven strategies.

Whether you are starting your career or pivoting to a new field, Monterrey’s dynamic economy rewards certified professionals. With expanding industrial innovation, tech-driven projects, and multinational investments, your training can open doors to impactful and well-paying roles across private and public sectors.

Python Statistics for Data Science Certification Training in Monterrey, Mexico

Python Statistics for Data Science Course Overview

Python Statistics for Data Science Course Topics

Understanding the Data

Probability and it's Uses

Statistical Inference

Testing the Data

Data Clustering

Regression Modelling

Why choose our Python Statistics for Data Science in Monterrey, Mexico?

Customer Satisfaction

Python Statistics for Data Science Frequently Asked Questions

Do you provide any group or corporate discounts for this training/course?

Whom do I contact to know more about the training program?

Do you provide discounts to unemployed individuals or students?

Do you provide placements or placement assistance after the course?

Python Statistics for Data Science Certification Training in Monterrey, Mexico

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Python Statistics for Data Science Course in other cities :

Python Statistics for Data Science Course Overview

Python Statistics for Data Science Course Topics

Understanding the Data

Probability and it's Uses

Statistical Inference

Testing the Data

Data Clustering

Regression Modelling

Why choose our Python Statistics for Data Science in Monterrey, Mexico?

Customer Satisfaction

Python Statistics for Data Science Frequently Asked Questions

Do you provide any group or corporate discounts for this training/course?

Whom do I contact to know more about the training program?

Do you provide discounts to unemployed individuals or students?

Do you provide placements or placement assistance after the course?

Python Statistics for Data Science Certification Training in Monterrey, Mexico

Explore More Certification Courses

R Statistics for Data Science

Data Science using R

Data Analytics with R

Tableau

Microsoft Power BI with Gen AI

Popular Courses

Scrum Master Certified (SMC)

SCRUMstudy Agile Master Certified (SAMC)

Lean Six Sigma Green Belt (LSSGB)

PMI - ACP®

Scrum Fundamentals Certified (SFC®)

Scrum Product Owner Certified (SPOC)

Lean Six Sigma Black Belt (LSSBB)

Scrum Developer Certified (SDC)

Python Statistics for Data Science Course in other cities :

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