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Course Description
The Data Analysis Using Python course is designed to equip learners with essential data analysis skills using Python’s powerful libraries such as NumPy, Pandas, Matplotlib, Seaborn, and Scikit-Learn. This course provides hands-on training in data manipulation, cleaning, visualization, exploratory data analysis (EDA), statistical analysis, and basic machine learning concepts.
By the end of this course, participants will be able to analyze, visualize, and derive insights from large datasets, making data-driven decisions in real-world scenarios.
Key Learning Objectives
By completing this course, participants will be able to:
- Introduction to Data Analysis & Python
- Data Manipulation Using NumPy & Pandas
- Data Visualization Using Matplotlib & Seaborn
- Exploratory Data Analysis (EDA) & Feature Engineering
- Working With Large Datasets & Databases
- Introduction to Statistical Analysis & Machine Learning
Prerequisites
To ensure a successful learning experience, participants should have:
- Basic Python programming (variables, loops, functions)
- Familiarity with basic mathematical and statistical concepts (helpful but not required).
- Interest in data analysis, data visualization, or data science applications.
No prior experience with Python or data analysis is required. This course starts from the basics and progressively builds towards advanced topics.
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Audience Profile
This course is ideal for:
- Aspiring Data Analysts & Data Scientists looking to build foundational Python skills.
- Students & Graduates seeking careers in data analytics, machine learning, or AI.
- Business Analysts who want to leverage Python for better data-driven insights.
- Software Developers interested in working with data processing and analytics.
- IT & Finance Professionals looking to automate data tasks and reporting.
- Beginners in Python Programming aiming to specialize in data analysis.
If you work with data and want to automate analysis, extract insights, or start a career in data science, this course is for you.
Career Growth & Industry Demand
Data analysis is a critical skill across industries, with organizations leveraging data-driven decision-making for business growth. Professionals skilled in Python for data analysis are in high demand, especially as companies move towards AI and machine learning-powered analytics.
Job Roles After Completing This Course
- Data Analyst
- Business Intelligence Analyst
- Data Scientist (Entry-Level)
- Financial Analyst
- Marketing & Customer Insights Analyst
- Research Analyst
Industries That Hire Python Data Analysts
- Finance & Banking (Risk analysis, investment forecasting)
- Healthcare & Pharmaceuticals (Medical data analysis, predictive modeling)
- Retail & E-Commerce (Customer insights, demand forecasting)
- Marketing & Advertising (Consumer behavior analysis, A/B testing)
- Technology & IT Services (Big data analytics, AI/ML applications)
- Manufacturing & Supply Chain (Logistics optimization, predictive maintenance)
Why Enroll in This Course?
- Beginner-Friendly Approach: Learn Python from scratch and progress to advanced analytics.
- Hands-On Learning: Work with real-world datasets and implement practical projects.
- Industry-Relevant Tools: Gain expertise in NumPy, Pandas, Matplotlib, Seaborn, and Scikit-Learn.
- Career Advancement: Get job-ready skills for data analysis roles across industries.
- Expert Instruction: Learn from experienced data analysts and Python professionals.
Whether you’re starting your journey in data analytics or looking to expand your skillset, this course equips you with practical Python skills to analyze data effectively.
Course Price
Group Learning
Learn with a group of peers in an interactive session-
Course Fees: ₹ 30,000
-
+ GST 18%: ₹ 5,400
-
Total Fees: ₹ 35,400
One-on-One Learning
Dedicated Training Sessions for Individuals-
Course Fees: ₹ 36,000
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+ GST 18%: ₹ 6,480
-
Total Fees: ₹ 42,480
Digital Self-Paced Learning
Access pre-recorded course materials for flexible, self-paced learning at your convenience.-
Course Fees: ₹ 6,500
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+ GST 18%: ₹ 1,170
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Total Fees: ₹ 7,670
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