Data Science with Python Training
Categories
Analytics and Data Management Certification
$199 – $2,099Price range: $199 through $2,099
$199
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LevelIntermediate
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Duration35 hours
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Last UpdatedMarch 3, 2026
Hi, Welcome back!
Pre-Requisites
- No prior programming or data science experience is mandatory
- Basic computer knowledge is sufficient to get started
- Participants must attend the complete 4-day training to receive the certificate
- Learners must complete and submit the assigned project for review to receive the Certification Guide Data Science certificate
- The course can be attended either in-person or through instructor-led online sessions
- Courseware will be shared through a download link with lifetime single-user access after download
- Registration confirmation and courseware access will be shared immediately after enrolment
- Classroom location and workshop details will be shared 5 days before the session; online joining details will be shared 24 hours before the class
- Exam fee is included in the course fee (exam access is provided on request via support)
- Assistance is provided for exam scheduling and system setup (for online exams)
- For rescheduling or cancellation, participants must contact
- and applicable fees may apply as per the refund policy
- Training is guaranteed to run and will not be cancelled by the provider
Who Should Enroll
- Beginners who want to start a career in data science or data analytics
- Professionals looking to specialize in data analytics using Python
- IT and software professionals planning to move into data-driven roles
- Engineers, analysts, and business professionals working with data
- Students and graduates interested in learning data science with Python
Courseware Includes
- 4 days of intensive in-person or instructor-led online training
- Comprehensive hands-on labs with Python
- Interactive statistical learning sessions (including advanced Excel usage)
- Certification Guide’s industry-designed courseware
- Real-world projects and case studies
- Assistance with exam tips and preparation
- 35 PDUs certificate
- Data Science with Python certification after successful project review
- Post-training support from certified staff
- 100% pass guarantee on the first attempt
Description
The Data Science with Python Training by Certification Guide is a hands-on, industry-focused program designed to take you from the fundamentals of data science to advanced analytics using Python. This course helps you learn how to work with complex data, perform statistical analysis, and build predictive models using real-world projects and business case studies.
The training is suitable for both beginners with no prior programming background and professionals who want to build or advance their careers in data analytics and data science. The program is delivered by experienced industry instructors and follows a practical learning approach to ensure strong real-world application.
What I will learn?
- Fundamentals of data science and data analytics
- Python programming for data analysis
- Working with data structures, functions, and classes in Python
- Statistical analysis using Python
- Predictive and analytical modeling techniques
- Data handling, preparation, and transformation
- Solving real business and research problems using Python
- Applying analytics techniques through real-world projects and case studies
- Hands-on practice with analytical workflows and tools
Course Agenda
Introduction
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Certification Guide, Instructor, Participant introduction and Set expectation by participant
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Introduction to Course
Introduction to Data Science
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What is Data Science?
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Analytics Landscape
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Life Cycle of a Data Science Project
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Data Science Tools & Technologies
Python Programming Language
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Python Basics
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Data Structures in Python
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Control & Loop Statements in Python
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Functions & Classes in Python
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Working with Data
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Analyze Data using Pandas
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Visualize Data
Statistics and Probability
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Measures of Central Tendency
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Measures of Dispersion
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Descriptive Statistics
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Probability Basics
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Marginal Probability
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Bayes Theorem
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Probability Distributions
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Hypothesis Testing
Advanced Statistics & Predictive Modeling
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ANOVA
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Linear Regression (OLS)
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Case Study: Linear Regression
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Principal Component Analysis
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Factor Analysis
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