Benefits of the course
- Python: Master data manipulation and analysis with Python.
- R Programming: Utilize R for statistical analysis and visualization.
- SQL: Acquire SQL skills for data extraction and management.
- Data Visualization: Create compelling visualizations.
- Machine Learning: Implement machine learning algorithms.
- Data Cleaning: Prepare and clean data for analysis.
- Statistical Analysis: Apply statistical techniques to data.
- Database Queries: Retrieve and manipulate data using SQL.
- Feature Engineering: Enhance model performance with feature engineering.
- Real-World Projects: Apply skills to practical data science projects.
- Communication: Effectively communicate data insights.
- Ethical Data Use: Understand ethical considerations in data science.
Topics for this course
43 Lessons
Introduction
What is Data Science
Application of Statistics and Programming in Data Science
Importance of Data in Al, Data Science and Data Analytics
Statistics
Python
DA with Python
R Programming
DA with R
Predictive Analysis
Machine Learning
Natural Language Processing(NLP)
Target Audience
- Aspiring data scientists seeking a versatile skill set.
- Data analysts looking to expand their toolkit.
- Programmers interested in data science using Python and R.
- Students and recent graduates aiming for data-related careers.
- Business professionals eager to harness data for insights.
- Researchers and scientists needing data analysis skills.
- Data enthusiasts wanting to deepen their expertise.
- Industry professionals across diverse sectors.
- Non-technical managers and decision-makers.