About Data Science Artificial Intelligence with Python Course
The program builds a foundation in Data Science with Python by training you on industry-standard tools and techniques through a practical, industry-oriented curriculum. This program requires no prior knowledge of coding in Python, R, or SQL and begins from fundamentals. By the end of the program, the candidates have a deep understanding of statistical techniques critical to Data Analysis and they are able to create Analytical models using real-life data to drive business impact.
Data analysis is the methodology of gathering data and processing it, in order to get useful insights. Data Analyst is all about the utilization of the major techniques, related to data visualization and manipulation. The techniques are used to expose the most valuable insights. These insights allow the companies to formulate better strategies and to make better decisions.
What you will learn
- Understand Python language basics and how they apply to data science.
- Practice iterative data science using Jupyter notebooks.
- Analyze data using Python libraries like pandas and NumPy.
- Create stunning data visualizations with matplotlib and seaborn.
- Build machine learning models using scipy and sci-kit learn.
- Demonstrate proficiency in solving real-life data science problems.
Top Skills You Will Learn as a Data Scientist
Job Opportunities in Data Science & Analytics
Who Is This Program For?
Minimum Eligibility for Data Science with Python
- Lectures 47
- Quizzes 0
- Duration 150 hours
- Skill level All levels
- Language English
- Students 368
- Assessments Yes
- Installation & Environment Setup Copy
- Interactive Shell & User interface or IDE Copy
- Variables & Data Types Copy
- Operators in Python Copy
- List Copy
- Tuple Copy
- Dictonaries Copy
- Numbers Copy
- Sets Copy
- Conditional Statements Copy
- Loops & User Input Copy
- Functions Copy
- File Handling Copy
- Exception Handling Copy
- Advance Oops Concepts & Application Copy
- Database Handling in Python Copy
- Multi threading Copy
Data Science with Python Basics
Algorithms & Analysis
- Numy Copy
- Panda Copy
- Data Visualization Copy
- Exploratory data analysis – Seaborn, Univariate, Bi Variate & Multivariate Analysis. Copy
- Linear Regression Copy
- Optimization Algorithm Copy
- Logistic Regression Copy
- Performance Measurement Copy
- KNN Copy
- Naive Bayes Algorithm Copy
- Decision Tree Classifier Copy
- Random Forest Classifier Copy
- Support Vector Machines Copy
- Time Series Analysis Copy
- Problem Statement and Analysis Copy
- Principal Component Analysis Copy