Data Science With Python
Learn Data Science, Machine Learning, Python Programming, Artificial Intelligence, Data Visualization, Statistical Analysis, and build real-world AI powered applications used across modern industries.
Complete Data Science Program
Beginner → Advanced Level Training
Course Overview
Data Science with Python involves using Python programming to analyze, process, visualize, and extract valuable insights from data. This course helps students understand modern data science workflows, machine learning algorithms, data preprocessing techniques, visualization tools, and artificial intelligence fundamentals. Students will learn Python programming, NumPy, Pandas, Matplotlib, Seaborn, machine learning, statistical analysis, NLP, deep learning basics, and real-world analytics projects. The course is designed for beginners, engineering students, analysts, developers, job seekers, and professionals who want to build strong careers in Data Science, AI, Analytics, and Machine Learning domains.
Course Syllabus
Variables & Data Types
Operators & Expressions
Conditional Statements
Loops & Functions
Modules & Packages
Object Oriented Programming
NumPy Arrays
Array Operations
Pandas DataFrames
Data Cleaning
Sorting & Filtering
Data Transformation
Matplotlib Basics
Scatter Plots & Histograms
Seaborn Visualization
Heatmaps & Pair Plots
Statistical Charts
Dashboard Design
Descriptive Statistics
Correlation Analysis
Outlier Detection
Distribution Analysis
Feature Analysis
Data Interpretation
Hypothesis Testing
T-Test & Chi-Square Test
ANOVA
Linear Regression
Model Evaluation
Statistical Reporting
Supervised Learning
Regression Models
Classification Models
Decision Trees
Random Forest Algorithms
Clustering Techniques
Cross Validation
Accuracy & Precision
Recall & F1 Score
ROC-AUC Curve
Confusion Matrix
Performance Metrics
Tokenization
Text Preprocessing
Stopword Removal
Sentiment Analysis
Text Classification
NLP Libraries
Neural Networks
Activation Functions
TensorFlow Basics
Keras Framework
Deep Learning Models
AI Project Workflows
Time Series Forecasting
Recommendation Systems
Big Data Basics
Apache Spark Introduction
Deployment Concepts
Real Industry Projects