Python Data Science Training in Vadodara - ATI

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 Include

• 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 Dee
• 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+ Year 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

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.