- Write basic Python programs for data handling and analysis.
- Use popular Python libraries like Pandas, NumPy, and Matplotlib to manipulate and visualize data.
- Clean and preprocess raw data for analysis.
- Perform exploratory data analysis to find meaningful patterns and insights.
- Create basic data visualizations such as charts and graphs to communicate findings.
- Understand and apply simple statistical concepts in data analysis.
- Work on real-world data projects and solve problems using Python.
- Prepare for entry-level roles like Data Analyst or Junior Data Scientist.
- Introduction to Data Science 00:35:08
- Python Basics till REPLACE 00:39:22
- Arrays 00:35:05
- Functions 00:23:45
- IF ELSE 00:17:16
- FOR LOOP 00:29:14
- WHILE LOOP 00:28:43
- Pattrens 00:17:57
- Python Lists 00:43:56
- Input 00:27:58
- Exploratory Data Analysis(EDA) 00:44:33
- Statistics Part-1 00:24:14
- Statistics Part-2 00:19:51
- Numpy Practical 00:39:50
- Basic computer skills: Comfortable using a computer, installing software, and navigating files and folders.
- No prior programming experience needed: This course starts from scratch with Python basics.
- Basic math understanding: Familiarity with high school-level algebra and statistics concepts will help but is not mandatory.
- Access to a computer with internet: To run Python programs and access course materials.
Course Description: Data Science using Python
This comprehensive course is designed to introduce beginners to the fundamentals of Data Science using Python. You will learn how to collect, clean, analyze, and visualize data through hands-on projects and real-world examples. The course covers essential Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn, alongside key data science concepts like data preprocessing, exploratory data analysis, and basic machine learning techniques.
By the end of this course, you will be equipped with the practical skills to work on data-driven projects and solve business problems using Python — a highly in-demand skill in today’s tech-driven world.
Expected Career Roles for Freshers
After completing this course, you can pursue entry-level roles such as:
Data Analyst
Responsible for interpreting data, generating reports, and helping organizations make data-backed decisions.Junior Data Scientist
Involved in data preparation, building basic predictive models, and supporting senior data scientists in projects.Business Intelligence (BI) Analyst
Focuses on transforming data into actionable business insights and dashboards.Data Engineer (Entry-Level)
Assists in data collection, transformation, and ensuring data pipelines are running smoothly.
Average Salary in India for Freshers (Approximate)
Data Analyst: ₹3.0 – ₹4.5 Lakhs per annum
Junior Data Scientist: ₹3.5 – ₹5.0 Lakhs per annum
BI Analyst: ₹3.0 – ₹4.5 Lakhs per annum
Entry-Level Data Engineer: ₹3.5 – ₹5.0 Lakhs per annum
This course is ideal for anyone looking to start a career in Data Science, Analytics, or related fields with Python as the core skill. No prior experience is required—just a keen interest in data and problem-solving.
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