About this Event
4-Day Weekend Data Science with Python Classroom Bootcamp
Begin your journey into Data Science with our engaging 4-Day Weekend Data Science with Python Classroom Bootcamp. This hands-on training program helps participants build practical knowledge in Python programming, data analysis, visualization, and introductory machine learning using real-world datasets.
During this instructor-led classroom training, learners will explore how to gather, organize, and analyze data while developing the ability to solve real business challenges through data-driven insights.
The program emphasizes experiential learning through coding exercises, guided labs, and project-based activities. By the end of the bootcamp, participants will understand how to convert raw data into valuable insights and build simple predictive models using Python — one of the most widely used tools in modern analytics.
This training blends theoretical concepts with practical industry examples to help professionals develop a solid understanding of modern data science workflows.
What You’ll Learn
Rather than focusing only on theory, this bootcamp prioritizes practical learning and hands-on implementation across the entire data science lifecycle.
- Python fundamentals for data science applications
- Data preparation and transformation using Pandas and NumPy
- Exploratory data analysis and visualization techniques
- Statistical methods to interpret data effectively
- Introduction to machine learning concepts using Scikit-learn
- Capstone project applying the full data science workflow
- Career guidance and resume preparation support
Data Science with Python Training Details
- 4 days of instructor-led weekend classroom sessions
- Hands-on labs using real-world datasets
- Mini capstone project for applied learning
- Python notebooks and study materials included
- Career mentoring and interview preparation
- Digital learning resources provided
Key Bootcamp Highlights
- Practical Python skills for data analytics
- Data cleaning, transformation, and visualization methods
- Introduction to machine learning fundamentals
- Project-based hands-on learning approach
- Industry-experienced trainers
- Interactive learning sessions with Q&A
- Certificate of completion
Who Should Attend?
This Data Science bootcamp is suitable for:
- Aspiring Data Scientists and Data Analysts
- IT professionals and software developers
- Business analysts and consultants
- Students and graduates interested in analytics
- Professionals planning a career shift into data-driven roles
Group Discount Offerings:
- 10% OFF for 3–5 participants
- 15% OFF for 6–10 participants
- 20% OFF for 15+ participants
4-Day Bootcamp Structure
Day 1: Python Fundamentals & Data Handling
Day 2: Data Cleaning, Wrangling & Visualization
Day 3: Statistics & Machine Learning Basics
Day 4: Predictive Modeling, Projects & Career Guidance
(A detailed agenda will be shared with registered participants.)
Why Learn Data Science with Python?
Python has become the most widely used programming language for data science, analytics, and machine learning. Organizations across industries rely on Python-based data solutions to drive decision-making, optimize operations, and build intelligent systems.
Learning data science with Python opens doors to high-demand careers in analytics, artificial intelligence, and business intelligence.
About iCert Global
iCert Global is a global provider of industry-aligned professional training in data science, analytics, IT, and emerging technologies. Their programs combine practical application with expert instruction, preparing professionals for high-demand roles in today’s data ecosystem.
Training We Also Offer:
PMP, Agile & Scrum, ITIL, Lean Six Sigma, CCNA, Cloud Computing, Cybersecurity, AI & Machine Learning and more.
For any queries related to the exam, location, course material or more, please connect on:
Phone: +1 713-287-1187
Email: Website: www.icertglobal.com
Day 1
🕑: 09:00 AM - 05:00 PM
Python Programming & Data Foundations
Info: Python setup & environment (Anaconda, Jupyter Notebook)
Python basics: variables, data types, control flow, functions
Working with lists, tuples, dictionaries, and sets
Data input/output and file handling
Introduction to NumPy for numerical computing
Hands-on: Data exploration with Python
Day 2
🕑: 09:00 AM - 05:00 PM
Data Wrangling & Visualization
Info: Data cleaning, filtering, and transformation with Pandas
Handling missing and duplicate data
Merging and concatenating datasets
Data aggregation and group operations
Visualization with Matplotlib and Seaborn
Practical exercises: Visual storytelling with charts and plots
Hands-on: Real dataset analysis
Day 3
🕑: 09:00 AM - 05:00 PM
Statistics & Machine Learning Essentials
Info: Descriptive statistics & inferential statistics
Probability concepts for analysis
Regression fundamentals (linear & logistic)
Evaluating model performance (accuracy, RMSE, ROC, confusion matrix)
Introduction to classification and clustering
Hands-on: Build & evaluate ML models using Scikit-learn
End-to-end mini ML project
Day 4
🕑: 09:00 AM - 05:00 PM
Advanced Analytics, Projects & Career Support
Info: Introduction to advanced concepts (feature engineering, model tuning)
Unsupervised learning fundamentals (K-Means, PCA)
Capstone mini project: from data collection to model building
Interpreting and presenting analytical results
Career roadmap & interview preparation tips
Q&A and revision session
Event Venue & Nearby Stays
600 N Congress Ave 14th floor, 600 North Congress Avenue, Austin, United States
USD 4870.17
