Python for Data Analytics and Machine Learning Bootcamp
In this program Course, you'll the necessary Python programming skills to manipulate databases and perform various levels of evaluation at the data.
Duration: 5 Days
Hours: 25 Hours
Training Level: All Level
About Python for Data Analytics Course:
Python for Data Analytics and Machine Learning Bootcamp enables you to take your data science skills into a variety of companies, helping them analyze data and make more informed business decisions. The course covers basic and advanced Python, data exploration, data visualization, descriptive analytics, and predictive analytics techniques with the Python language. You will learn about various Python packages like Numpy, Pandas, Scikit Learn, and Seaborn. You will also get a chance to learn how to import and export data using Python, data structures in Python, various statistical concepts, cluster analysis, Regression, and classification.
Python for Data Analytics Course Objective:
- Install Python, and Jupyter Notebook and learn about the various Python packages
- Gain an in-depth understanding of data structure used in Python and learn to import/export data in Python
- Define, understand, and use the various functions in Python
- Learn to do data visualization using Python packages like Matplotlib and Seaborn
- Gain a basic understanding of various statistical concepts
- Understand and use linear regression models, and classification techniques in Machine Learning
- Learn and use clustering methods including k-means and hierarchical clustering
Who is the Python for Data Analytics Course Target Audience?
- This course is meant for all those students and professionals who are interested in using Python's powerful ecosystem
What Basic Knowledge is Required to Learn Python for Data Analytics?
- There are no prerequisites
Curriculum
Total Duration: 25 Hours
Basic and Advanced Python
- Introduction to Python
- Various data types in Python
- Lists
- Tuples
- Dictionaries
- Sets
- Core programming concepts
- While Loops
- For Loops
- If Else statements
- Functional Programming using Python
- How to create the functions
- Benefits of using the functions
- Text Processing using the RE module
- Introduction to String Operations and RE Module
- Exception Handling in Python
- Understand exception Handling using Python
- Understand the TRY-EXCEPT-ELSE-FINALLY block
Data Manipulation and Analytics using Python
- Objects in Python
- Matrix
- Data frames
- Visualizations in Python
- Packages in Python
- Numpy
- Matplotlib
- Pandas
- Matrix operations
- Dataframes
- Joins and manipulations in Dataframes
Machine Learning
- Data Pre-processing
- Missing Data
- Categorical Data
- Feature Scaling
- Data Split (Test and Training Set)
- Regression
- Simple Linear Regression
- Multiple Linear Regression
- Classification
- Logistic Regression
- K Nearest Neighbours (K-NN)
- Support Vector Machine (SVM)
- Naive Bayes
- Decision Tree Classification
- Random Forest Classification
- Clustering
- K Means
- Hierarchical Clustering
- Association Rule Mining
- Apriori
- Model selection and Boosting
- K Fold Technique
- Grid Search