Learn Data Science With Python
Our Data Science with Python course teaches you how to use Python’s powerful ecosystem to analyze and visualize data. While learning statistical analysis methods, you will master data manipulation in Panda, numerical computation in NumPy, and visualization in Matplotlib/Seaborn.
Skills You’ll Gain:
- Python programming for data science
- Data wrangling with Pandas and NumPy
- Statistical analysis and visualization
- Machine learning algorithms
- Dimensionality reduction techniques
- Time series analysis
- Database integration and Tableau visualization
Module 1 - Introduction to Data Science and ML using Python
- Overview of Python
- Applications of Python
- Python Scripts on UNIX/Windows
- Variables, Loops, and Conditionals
- Data Science Lifecycle
Module 2 - Data Handling, Sequences and File Operations
- Data Analysis Pipeline
- Data Wrangling
- Python I/O Operations
- Strings, Lists, Dictionaries
- Sets and Tuples
Module 3 - Functions, OOPs, Modules, Errors, and Exceptions
- Functions and Lambda
- Object Oriented Concepts
- Standard Libraries
- Error Handling
- Package Installation
Module 4 - Introduction to NumPy, Pandas, and Matplotlib
- NumPy Arrays
- Pandas DataFrames
- Data Visualization
- Reading Excel/CSV
- Plot Customization
Module 5 - Data Manipulation
- Merging and Concatenation
- Joins and Analysis
- Dataset Exploration
- Basic Data Operations
Module 6 - Supervised Learning - I
- Classification Use Cases
- Decision Trees
- Random Forest
- Confusion Matrix
Module 7 - Dimensionality Reduction
- PCA
- Factor Analysis
- Scaling Models
- LDA
Module 8 - Association Rules and Recommendation Systems
- Association Rule Parameters
- Collaborative Filtering
- Content-Based Filtering
- Recommendation Engines
Module 9 - Time Series Analysis
- TSA Components
- ARIMA Model
- Stationarity
- ACF & PACF
Module 10 - Database Integration with Python
- Python MySQL
- CRUD Operations
- MongoDB Queries
- Index Management
Module 11 - Data Visualization in Tableau
- Basic Charts
- Calculations
- Dashboards
- Geographic Maps
Earn a recognized credential that validates your technical expertise and opens doors to new career opportunities.
Why Learn Data Science With Python?
- Python’s simplicity and readability
- Extensive data science libraries
- Good for prototyping and production
- Strong visualization capabilities
- Integration with big data tools
- Good job market demand
- Active community support
- Cross-platform compatibility
- Good for machine learning integration
- Continuous ecosystem growth
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