About Data Science Course
This comprehensive course is designed to equip aspiring data scientists with the essential skills and tools needed to unlock the potential of data, extract valuable patterns, and make data-driven decisions that drive innovation and growth.
The Data Science course is a dynamic and immersive program that takes participants on a journey from data wrangling to predictive modeling. Throughout this course, students will delve into the diverse disciplines of data science, including data analysis, machine learning, and data visualization.
Course Duration: 9 Months
Internship: 2 Months
In this course you will get
- Daily 2 Hrs Practical Training (Offline)
- Project Assignments
- Freelancing and Business Start-up training
- Interview & Personality Training
- Internship Facilities
- 100% Job Placement Guarantee
Course Modules
Data Science (AI - ML)
Data Science (AI - ML)
- Introduction to Data Science: Explore the fundamental concepts and principles of data science, understanding its impact across industries.
- Data Acquisition and Cleaning: Learn the art of data collection, cleansing, and preprocessing, ensuring data quality for analysis.
- Exploratory Data Analysis (EDA): Discover techniques to explore and summarize data, identifying patterns, and gaining valuable insights.
- Data Visualization: Master data visualization tools and libraries, creating compelling visual representations to communicate data findings effectively.
- Machine Learning: Dive into the world of machine learning algorithms, developing predictive models for classification and regression tasks.
- Model Evaluation and Optimization: Understand how to evaluate model performance and fine-tune algorithms for better accuracy and efficiency.
- Big Data and Cloud Computing: Explore big data technologies and cloud platforms, harnessing the power of distributed computing for large-scale data processing.
- Natural Language Processing (NLP): Unlock the potential of NLP techniques to analyze and interpret human language data.
- Real-World Projects: Engage in hands-on projects, applying your data science knowledge to solve real-world problems and gain practical experience.
- Ethical Considerations: Address ethical implications of data science, ensuring responsible and transparent use of data for societal benefit.
- Computer Vision, Power BI (Business Intelligence), Web Scraping and Automation, Time Seriece Forecasting.
