Data Science with Phython Training in Rancho Santa Margarita, CA

Become a job-ready data professional by learning Python, data analysis, visualization, and basic machine learning using real datasets and hands-on labs.

Advance your career with our 4-day Data Science with Python Classroom Training, designed to help you become proficient in data handling, analytical techniques, and predictive modeling using Python — one of the most in-demand skills in the analytics industry.

This industry-focused bootcamp blends practical coding, applied analytics, and project work, empowering you to work confidently with real business data and make data-driven decisions.

Rather than just theory, this bootcamp immerses you in practical Python-driven data science workflows — from data ingestion to interpretation and model building:

• Python Fundamentals for Data – Learn Python programming essentials and setup for data tasks.
• Data Manipulation & Wrangling – Use Pandas & NumPy to clean, transform, and summarize datasets.
• Exploratory Data Analysis & Visualization – Visualize data insights using Matplotlib & Seaborn.
• Statistical Analysis – Apply descriptive & inferential statistics to interpret data.
• Machine Learning Basics – Build and evaluate regression and classification models with Scikit-learn.
• Capstone Project – Apply a complete data science lifecycle project using real data.
• Career Preparation – Guidance on data science roles, interview tips, and resume focus.

• 4 Days of instructor-led classroom training
• Hands-on labs with real datasets
• Mini capstone project
• Study materials and code notebooks
• Career mentoring and interview guidance
• Soft copy resources included

• Practical Python programming for analytics
• Data cleaning, wrangling & visualization
• Machine learning foundations
• Project-centric hands-on labs
• Expert instructors with real industry experience
• Interactive sessions & Q&A
• Certificate of completion
  

• 10% OFF for 3–5 participants
• 15% OFF for 6–10 participants
• 20% OFF for 15+ participants
  

Ideal for:

• Aspiring Data Scientists & Analysts
• IT & Software Professionals targeting data roles
• Business Analysts & Consultants
• Students & fresh graduates
• Professionals looking to transition into analytics

Day 1: Python & Data Handling
Day 2: Data Cleaning & Visualization
Day 3: Statistics & Machine Learning Concepts
Day 4: Advanced Modeling, Projects & Career Guidance

(Detailed agenda available on next Page.)

Python is the world’s leading language for data analysis and machine learning roles, widely used in analytics, business intelligence, and AI roles. As organizations become data-driven, Python data science skills open doors to high-growth careers.

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.

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: [email protected]

Website: www.icertglobal.com

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

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

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

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

Know what’s Happening Next — before everyone else does.

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Host or Publisher iCertGlobal