25% Discount For All Pricing Plans "welcome"
Up to 12 Members
Each class is limited to 12 members, ensuring personalized attention and an interactive learning experience.
+50 Projects
Gain hands-on experience with over 50 real-world projects, designed to solidify your data analysis skills.
+30 In Class Works
Participate in more than 30 in-class activities, enhancing your practical understanding through collaborative exercises.
1-1 Support
Receive dedicated 1-on-1 support from experienced mentors, tailored to address your specific learning needs.
Introduction to Python and Programming Basics
Start by learning the fundamentals of Python, covering variables, data types, loops, and conditionals. This foundation is crucial for understanding how to manipulate and analyze data effectively. Whether you're new to coding or just brushing up, this topic sets the stage for success in data analysis.
Functional Programming and Data Manipulation with Numpy
Explore functional programming in Python and gain hands-on experience with the Numpy library. Learn how to handle arrays, perform mathematical operations, and manipulate data structures efficiently, making complex data analysis tasks more approachable.
Data Handling and Analysis with Pandas
Dive deep into Pandas, the go-to library for data analysis in Python. This topic covers how to read, clean, and process datasets, work with DataFrames, and perform essential data operations such as filtering, sorting, and grouping, equipping you with the tools needed for robust data analysis.
Data Cleaning and Handling Missing Data
Data cleaning is one of the most critical steps in any analysis. Learn techniques for dealing with missing values, removing outliers, and preparing datasets for deeper analysis. This topic ensures that you can work confidently with real-world, messy datasets.
Data Visualization with Matplotlib and Seaborn
Master the art of data visualization using Matplotlib and Seaborn. You'll create a wide range of plots, from basic bar and line charts to advanced visualizations like heatmaps and pair plots, helping you present your data insights effectively and clearly.
Exploratory Data Analysis (EDA)
Exploratory Data Analysis (EDA) enables you to uncover patterns, relationships, and anomalies in your datasets. You'll learn how to perform EDA with Python to extract valuable insights that set the foundation for further analysis or modeling.
Introduction to Statistics for Data Analysis
This topic introduces key statistical concepts necessary for data analysis, such as distributions, hypothesis testing, and summary statistics. Through practical applications in Python, you'll learn how to interpret data and make informed, data-driven decisions.
Final Project and Application
Put all your new skills into practice with a comprehensive data analysis project. You’ll choose a dataset, clean and process the data, perform analysis, create visualizations, and present your findings, showcasing the full spectrum of your abilities developed throughout the course.
Topics Covered
Python Fundamentals and Data Structures
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Python Basics: Introduction to Python programming, covering syntax, variables, data types, and operators.
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Control Flow and Loops: Learn how to implement loops and conditionals for controlling the flow of programs.
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Data Structures: Explore essential Python data structures like lists, tuples, sets, and dictionaries for data manipulation.
Program
Contact Us for More Details
If you have any questions or would like more information about the Python for Data Analysis training program, feel free to reach out to us. We’re happy to assist you with any inquiries, registration details, or clarifications about the course content and structure.
Program Details
Python For Data Analysis is an intensive, hands-on training program designed for beginners who want to develop skills in data analysis using Python. This course covers essential Python libraries and techniques for analyzing, cleaning, and visualizing data, making it ideal for those pursuing a career in data science or business analytics.
By the end of this course, participants will be able to confidently analyze datasets, perform data cleaning, and create insightful visualizations, all while preparing themselves for more advanced data science concepts.
Dates
A new class is opened every month for this training program.
Duration
This training program consists of 12 weeks of intensive study.
Way to Learn
Lessons are held completely online and live via Google Meet or Zoom.
Method
This consists of 24 courses in total, including theoretical, practical sessions.