Data Science Course with Advanced Python & AI/ML Training
Looking to build a career in Data Science?
Our Data Science Course with Advanced Python and AI/ML Training is designed to help you master data analysis, machine learning, and artificial intelligence skills. Learn from industry experts and work on real-time projects to become a job-ready data scientist.
This course covers everything from Python programming for data science to advanced machine learning algorithms, making it ideal for beginners and professionals aiming to upgrade their skills.
Course Title:
Advanced Python for Data Science Training
Duration:
60 Hours
Description:
Master Advanced Python for Data Science and learn how to analyze, process, and visualize data efficiently. This module helps you build a strong foundation in Python programming with a focus on real-world data applications.
Gain hands-on experience with popular libraries like NumPy, Pandas, Matplotlib, and Seaborn, and learn how to handle large datasets with ease.
Key Highlights:
- Advanced Python programming concepts
- Data analysis using NumPy & Pandas
- Data cleaning and preprocessing techniques
- Data visualization with Matplotlib & Seaborn
- Exploratory Data Analysis (EDA)
- File handling and automation
- Real-time mini projects
Course Title
Artificial Intelligence and Machine Learning Course
Duration:
60 Hours
Description:
Become an expert in Artificial Intelligence and Machine Learning with our industry-focused training program. Learn how to build predictive models, analyze data patterns, and develop intelligent systems used in real-world applications.
This module covers essential ML algorithms, model evaluation techniques, and an introduction to deep learning, making you job-ready for AI and data science roles.
Key Highlights:
- Introduction to Artificial Intelligence & Machine Learning
- Supervised and Unsupervised Learning
- Regression and Classification algorithms
- Decision Trees and Random Forest
- Clustering techniques (K-Means)
- Model evaluation and performance tuning
- Basics of Deep Learning
- Real-time projects and case studies.