Python Data Science Training : Step By Step For Beginners to Advanced

Python Data Science Training Overview

Python Data-Science training equips individuals with the skills to analyze, visualize, and derive insights from data using Python's powerful libraries and tools.

Prerequisites

Basic Python Knowledge
Basic Mathematics and Statistics
Familiarity with Data Structures
Computer Literacy
Optional but Beneficial

Python Data-Science Includes

Introduction to Data Science and Python
Python Programming Refresher
Data Manipulation with Pandas
Numerical Computing with NumPy
Data Visualization
Exploratory Data Analysis (EDA)
Statistical Analysis
Machine Learning with Scikit-Learn
Advanced Topics in Machine Learning
Introduction to Deep Learning
Working with Real-World Data
Capstone Projects and Case Studies
Version Control and Collaboration
Best Practices and Industry Standards

Key Highlights

Personal Coaching
Industry Experts with 15+ Years Experience
Morning, Noon, Evening Batch Timings
Training with Internship (Live Project Working)
Career Guidance

Course Content

Tools and Techniques:

Books
Online Courses
Documentation and Tutorials
Community Forums

Key Concepts of Python Data Science:

Data Science Workflow
Python Libraries
Basic Python Programming
Data Manipulation with Pandas
Data Visualization
Machine Learning with SciKit Learn
Deep Learning
Statistical Analysis

Development Environment :

Integrated Development Environment(IDEs)
Package Management

Learning Path :

Basic Python
Data Manipulation with pandas
Data Visualization
Statistics and Probability
Machine Learning
Deep Learning
Project Work
Advanced Topics

Python for Data Analysis - Numpy:

Welcome to the NumPy Section!
Introduction to Numpy
Numpy Arrays
Quick Note on Array Indexing
Numpy Array Indexing
Numpy Operations
Numpy Exercises Overview
Numpy Exercises Solutions

Introduction to Data Visualization:

Some Theoretical Principles Behind Data Visualization
Histograms-Visualize the Distribution of Continuous Numerical Variables
Boxplots-Visualize the Distribution of Continuous Numerical Variables
Scatter Plot-Visualize the Relationship Between 2 Continuous Variables
Barplot
Pie Chart
Line Chart

Statistical Data Analysis - Basic:

Some Pointers on Exploring Quantitative Data
Explore the Quantitative Data: Descriptive Statistics
Grouping & Summarizing Data by Categories
Visualize Descriptive Statistics-Boxplots
Common Terms Relating to Descriptive Statistics
Data Distribution- Normal Distribution
Check for Normal Distribution
Standard Normal Distribution and Z-scores
Confidence Interval-Theory
Confidence Interval-Calculation

Python for Data Analysis - Pandas:

Welcome to the Pandas Section!
Introduction to Pandas
Series
DataFrames
Missing Data
Groupby
Merging Joining and Concatenating
Operations
Data Input and Output

Python for Data Visualization - Matplotlib:

Matplotlib Part 1
Matplotlib Part 2
Matplotlib Part 3
Matplotlib Exercises

Python for Data Visualization - Seaborn:

Introduction to Seaborn
Categorical Plots
Matrix Plots
Grids
Style and Color
Seaborn Exercise

Python for Data Visualization - Pandas Built-In Data Visualization:

Pandas Built-in Data Visualization
Pandas Data Visualization Exercise

Introduction to Machine Learning:

Welcome to Machine Learning. Here are a few resources to get you started!
Supervised Learning Overview
Machine Learning with Python

Linear Regression:

Linear Regression Theory
model_selection Updates for SciKit Learn 0.18
Linear Regression with Python

Logistic Regression:

Logistic Regression Theory
Logistic Regression with Python
Logistic Regression Project

K Nearest Neighbours:

KNN Theory
KNN with Python
KNN Project Overview
KNN Project Solutions

KNN Project Solutions

Introduction to Tree Methods
Decision Trees and Random Forest with Python
Decision Trees and Random Forest Project

Support Vector Machines:

SVM Theory
SVM with Python
SVM Project

SVM Project Solutions

K Means Algorithm Theory
K Means with Python
K Means Project

Natural Language Processing:

Natural Language Processing Theory
NLP with Python
NLP Project

Road Map — Python Data Science Training

Step-by-step learning path from Python basics to real-world projects

1. Python Basics & Refresher
2. Data Structures & Functions
3. NumPy for Numerical Computing
4. Data Manipulation with Pandas
5. Data Visualization (Matplotlib & Seaborn)

6. Exploratory Data Analysis (EDA)
7. Statistics & Probability
8. Machine Learning with scikit-learn
9. Introduction to Deep Learning
10. Capstone Projects & Case Studies

Your Instructor

Learn from an industry expert with proven excellence in training, consulting, and mentoring.

Mr. Adarsh Patel

Corporate Trainer & Business Consultant 15+ Years Experience

Education: MCA (2009), B.Com (Computer) (2006)

Experience: Over 15 years delivering corporate training, consulting, and mentoring across IT and digital transformation domains.

Recognized for designing practical, project-based learning experiences and helping 2000+ students & professionals build strong careers in technology.

Programming: PHP, Python, Java, C/C++, Dart, Android Development
Frameworks: Laravel, ReactJS, Flutter, ASP.NET
Databases: MySQL, MongoDB, SQL Server, Oracle
Digital Tools: SEO, CRM, ERP, WordPress, AI Tools (ChatGPT, Gemini)
Special Skills: Software Consulting, Digital Marketing, Project Management

Delivered 200+ Expert Lectures and 80+ Workshops across universities, training institutes, and corporate organizations. Medium of Communication will be in English, Hindi or Gujarati.

Hands-on coding bootcamps for web and app development
Industry seminars on ERP, CRM, and Digital Transformation
Special workshops for entrepreneurs on business automation

Advised startups and enterprises on technology adoption, ERP/CRM solutions, and workflow automation.

150+ consulting assignments with SMEs and corporates
Expert in business process mapping and software deployment
Guided companies on digital marketing and automation strategy

Recognized with multiple Appreciation Certificates from universities and corporates
Collaborated with 50+ organizations for training & development
Trained 2000+ students and professionals successfully
Invited as keynote speaker at IT summits and business forums

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Frequently Asked Questions

What prerequisites are needed for this Python Data Science Training?

Having basic Python knowledge, mathematics & statistics fundamentals, and general computer literacy is recommended, but not mandatory.

What topics does the course cover?

The course covers Python basics, data manipulation with Pandas, numerical computing with NumPy, data visualization, exploratory data analysis, statistics, machine learning with scikit-learn, and an introduction to deep learning.

What is the learning path of this course?

The learning path starts with Python basics, then moves to NumPy, Pandas, data visualization, EDA, statistics, machine learning, deep learning, and concludes with capstone projects.

What are the key highlights of the training?

Key highlights include expert faculty with 15+ years of experience, flexible batch timings, live projects, hands-on training, internships, and dedicated career guidance.

What career roles can I pursue after this training?

You can pursue roles such as Data Scientist, Data Analyst, Machine Learning Engineer, AI Engineer, Data Engineer, or Python Data Scientist.

Is there a demo lecture available?

Yes, you can request a free demo lecture before enrolling. Training is available in classroom, online, or recorded formats.

What are the fee structures?

Fees depend on the type of batch (regular, weekend, group, or industrial training). Regular 3-month courses start at ₹15,000.

Do I get a certificate after completion?

Yes, you will receive a recognized certification upon successfully completing the training program.

Are there any student testimonials available?

Yes, you can view recent student feedback and testimonials on the training page itself.

How do I enroll or get more details?

You can enroll by booking your seat online or contacting us at +91 93749 69705 or email contact@arthtraininginstitute.com.

You are eligible for the following post after Training

Data Scientist
Data Analyst
Machine Learning Engineer
Python Data Analyst
Python Data Scientist
AI Engineer
Research Scientist (Data)
Senior Data Scientist
Python ML Engineer
Data Engineer

Request for Free Demo Lecture

Fees Structure

Fees Structure will be depends on the what type of course you are joining, for example if you are joining for regular batch for 3 month course then fees will be 15000/- if you are joining in group then fees discount will be applicable, for weekend batch fees will be different, For Faculty Development Program and Industrial Training Fees will be different.