Data Science Course
Master data analysis, machine learning, and statistical techniques
Course Information
- Duration: 6 Months
- Modules: 8
- Mode: Classroom/Online
- Certification: Yes
- Placement Assistance: Yes
- Project Work: Included
Data Science Training Program
Our comprehensive Data Science course equips you with the skills to analyze complex data sets, build predictive models, and extract meaningful insights. Learn statistical analysis, machine learning, and data visualization through hands-on projects and real-world case studies.
Key Features
- Hands-on experience with data analysis tools
- Real-world project implementation
- Machine learning algorithms
- Statistical analysis techniques
- Data visualization tools
- Industry case studies
Course Curriculum
Module 1: Python Programming
- Python basics and data structures
- NumPy and Pandas
- Data manipulation
- Python for data analysis
Module 2: Statistics and Mathematics
- Descriptive statistics
- Probability theory
- Inferential statistics
- Linear algebra basics
Module 3: Data Preprocessing
- Data cleaning
- Feature engineering
- Data transformation
- Handling missing data
Module 4: Machine Learning
- Supervised learning
- Unsupervised learning
- Model evaluation
- Feature selection
Module 5: Deep Learning
- Neural networks
- Deep learning frameworks
- CNN and RNN
- Transfer learning
Module 6: Data Visualization
- Matplotlib and Seaborn
- Interactive visualizations
- Dashboard creation
- Storytelling with data
Module 7: Big Data Analytics
- Big data concepts
- Hadoop ecosystem
- Spark fundamentals
- Data warehousing
Module 8: Capstone Project
- Project planning
- Data collection and analysis
- Model development
- Project presentation
Career Opportunities
After completing this course, you can pursue careers as:
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Business Intelligence Analyst
- Data Science Consultant
- Research Scientist
Prerequisites
Basic understanding of mathematics and programming concepts. Knowledge of Python programming is beneficial but not mandatory. Strong analytical and problem-solving skills are essential.
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