Python for Data Science
Master Data Analysis, Machine Learning & AI with Python
Course Overview
🎯 Course Objective
Master Python programming for data science, machine learning, and AI applications. Learn to analyze data, build predictive models, and create intelligent solutions using industry-standard tools and libraries.
⏱️ Duration & Schedule
12-week comprehensive program with 3 sessions per week. Each session is 2 hours long with hands-on coding practice and real-world data science projects.
💼 Career Prospects
Prepare for roles like Data Scientist, Machine Learning Engineer, Data Analyst, AI Developer, and Research Scientist. Includes interview preparation and placement assistance.
🏆 Certification
Receive industry-recognized certification upon successful completion with portfolio of data science projects and practical assessments.
Meet Your Instructor
Trilochan Tarai
Data Science Expert
With over 20 years of experience in data science and machine learning, Trilochan has worked with leading tech companies like TCS and Majesco. He specializes in Python, data analysis, machine learning, and AI applications, and has mentored over 40000+ students in their data science journey.
Course Curriculum
Module 1: Python Fundamentals for Data Science
Duration: Week 1-2 | Topics: 8 sessions
- Python Basics and Data Types
- Control Structures and Functions
- Object-Oriented Programming in Python
- File Handling and Exception Handling
- Python Libraries for Data Science
- NumPy for Numerical Computing
- Pandas for Data Manipulation
- Data Visualization with Matplotlib
Module 2: Data Analysis and Visualization
Duration: Week 3-4 | Topics: 8 sessions
- Data Cleaning and Preprocessing
- Exploratory Data Analysis (EDA)
- Statistical Analysis with Python
- Advanced Visualization with Seaborn
- Interactive Visualizations with Plotly
- Data Wrangling Techniques
- Time Series Analysis
- Data Storytelling and Presentation
Module 3: Machine Learning Fundamentals
Duration: Week 5-6 | Topics: 8 sessions
- Introduction to Machine Learning
- Supervised Learning Algorithms
- Unsupervised Learning Techniques
- Model Evaluation and Validation
- Feature Engineering and Selection
- Cross-validation and Hyperparameter Tuning
- Ensemble Methods
- Model Deployment and Monitoring
Module 4: Advanced Machine Learning & AI
Duration: Week 7-8 | Topics: 8 sessions
- Deep Learning with TensorFlow/Keras
- Neural Networks and Deep Learning
- Natural Language Processing (NLP)
- Computer Vision and Image Processing
- Reinforcement Learning Basics
- AI Model Optimization
- Transfer Learning
- AI Ethics and Responsible AI
Module 5: Big Data and Cloud Computing
Duration: Week 9-10 | Topics: 8 sessions
- Big Data Processing with Spark
- Cloud Computing for Data Science
- Database Management and SQL
- NoSQL Databases (MongoDB, Cassandra)
- Data Pipeline Development
- Streaming Data Processing
- Containerization with Docker
- Scalable Machine Learning Systems
Module 6: Projects & Portfolio Development
Duration: Week 11-12 | Topics: 8 sessions
- End-to-End Data Science Project
- Predictive Analytics Project
- Machine Learning Model Deployment
- Data Science Portfolio Creation
- Git and Version Control for Data Science
- Jupyter Notebook Best Practices
- Presentation and Communication Skills
- Interview Preparation and Mock Interviews
Why Choose This Course?
Comprehensive Curriculum
From Python basics to advanced AI applications, covering everything needed for a successful data science career
Hands-on Practice
Live coding sessions, assignments, and real-world data science projects with industry datasets
Industry-Focused
Learn data science skills that are in high demand in the current job market with practical applications
Small Batch Size
Maximum 25 students per batch for personalized attention
Placement Support
Interview preparation and job placement assistance for data science and AI roles
Lifetime Support
Continued mentor support even after course completion
Ready to Master Python for Data Science?
Join hundreds of successful data scientists who advanced their careers with Python and AI skills