Data Science with Python
Data Science with Python
This course teaches you how to use Python for data science tasks like data analysis, visualization and machine learning. It is ideal for beginners who want to enter the data science field.
Course Type:
Cloud & DevOps
Certificate:
Yes
Job Placement:
Yes
Length (Weeks):
12
Prerequisites:
Basic Python Knowledge
Class Type :
Class Room / Online
Batch Size:
30
Level:
Intermediate
Course Syllabus
- What is Data Science?
- Data Science Lifecycle
- Applications of Data Science
- Role of a Data Scientist
- Tools used in Data Science
- Introduction to Python
- Installing Python and Jupyter Notebook
- Variables, Data Types, and Operators
- Conditional Statements & Loops
- Functions and Lambda Expressions
- Python Collections: List, Tuple, Dictionary, Set
- Exception Handling
- File Handling
NumPy
- Arrays and Vectorized Operations
- Indexing, Slicing and Reshaping
Pandas
- DataFrames and Series
- Reading and Writing Data (CSV, Excel, etc.)
- Data Cleaning and Manipulation
Matplotlib and Seaborn
- Data Visualization Basics
- Customizing Plots and Charts
- Advanced Graphs with Seaborn (Boxplots, Heatmaps, Pairplots)
- Handling Missing Data
- Encoding Categorical Variables
- Feature Scaling (Normalization and Standardization)
- Feature Engineering Basics
- Outlier Detection and Treatment
- Understanding Distributions
- Correlation and Causation
- Univariate, Bivariate, and Multivariate Analysis
- Summary Statistics and Visual Storytelling
- Descriptive Statistics
- Probability Basics
- Distributions: Normal, Binomial, Poisson
- Hypothesis Testing
- p-values and Confidence Intervals
- ANOVA and Chi-Square Test
- Types of Machine Learning: Supervised vs Unsupervised
- ML Workflow
- Train-Test Split and Cross-Validation
- Performance Metrics (Accuracy, Precision, Recall, F1-Score)
- Linear Regression
- Logistic Regression
- Decision Trees and Random Forest
- Support Vector Machines (SVM)
- K-Nearest Neighbors (KNN)
- Naive Bayes
- K-Means Clustering
- Hierarchical Clustering
- Dimensionality Reduction (PCA)
- Confusion Matrix
- ROC and AUC
- Cross-Validation
- Hyperparameter Tuning with GridSearchCV and RandomSearchCV
- Text Preprocessing (Tokenization, Stopwords, Lemmatization)
- Bag of Words and TF-IDF
- Sentiment Analysis
End-to-End Data Science Projects
- Customer Churn Prediction
- House Price Prediction
- Credit Card Fraud Detection
- E-commerce Sales Forecasting
- Movie Recommendation System
Working with Real Datasets (Kaggle / UCI)
- Git Basics: Clone, Commit, Push, Pull
- Using GitHub to Host and Share Code
- Creating Repositories for Projects
3
Start Date:
2025-04-15
Schedule:
Weekdays
Session Timings:
Seats Status:
Available
EMI Available:
Yes
Join a Free Demo – Get Career-Ready in Just 3 Months!
Key Features
Chedy Technologies delivers comprehensive Selenium with Java training across 27+ branches, led by seasoned professionals. Here's what makes us stand out:
- 40+ Hours of In-Depth Course Content
- Learn from Industry-Experienced Trainers
- Successfully Trained Over 500+ Batches
- 100% Career-Focused, Job-Oriented Program
- Attend a Free Demo Class Before You Decide
- Hands-On Support for Certification Preparation
- Partnerships with Global Tech Leaders
- Flexible Training Modes: Classroom, Online & 1-to-1
Our Global Technology Partnerships
Chedy Technologies is an Authorized Training Partner with leading tech organizations including Oracle, Microsoft, Pearson VUE, PSI, and AWS. These collaborations ensure that our students receive internationally recognized certifications and industry-relevant skills.