--- title: Descriptive Analytics & Data Pre-Processing with Python | Amity Online description: Enhance your data science skills with a certification in Descriptive Analytics and Data Pre-Processing using Python. Learn from industry experts at Amity Online. --- # Certificate in Descriptive Analytics and Data Pre-processing using Python Post successful completion, apply for paid internship In Collaboration With Step into the world of data analytics with a Certificate in Descriptive Analytics and Data Pre-processing Using Python. This course is meticulously designed to transform beginners and enthusiasts into proficient data analysts. With hands-on projects, industry-relevant tools, and expert guidance, you’ll gain the skills needed to clean, transform, and analyze data, turning raw information into actionable insights. Whether you're preparing for a career in analytics or upskilling, this course is your gateway to success. **Core Foundations:** Delve into the fundamentals of descriptive analytics and data preparation. **Python Expertise:** Gain proficiency in Python libraries like Pandas, NumPy, and Matplotlib. **Data Cleaning and Transformation:** Learn to handle missing values, engineer features, and prepare datasets for analysis. **Exploratory Analysis:** Explore univariate, bivariate, and multivariate statistical methods. **Industry Insights:** Learn from experts with extensive experience in analytics and AI. **Internship Opportunities:** Apply for a paid internship after you complete the program. **Flexible Learning:** Learn anytime, anywhere with our expert-led recorded lectures. \*Paid internship will be as per organization's norms or on a first-come, first-serve basis. Hurry! First batch intake closes on 30 Aug 2026 — only 5 internship spots left! ## Skills you'll gain ### Data Manipulation Efficiently handle and transform datasets. ### Data Cleaning Prepare accurate and reliable data. ### Feature Engineering Create impactful features for analysis. ### Exploratory Analysis Uncover insights through statistical methods. ### Data Wrangling Organize and aggregate data effectively. ### Data Visualization Present insights through impactful visual representations. ### Statistical Analysis Apply statistical techniques for data interpretation. ### Corporate Paid Internship Gain real-world professional experience through an internship\*. ## Tools and Platforms covered ### 1\. Introduction to Python for Data Analytics Develop a strong foundation in Python for data science by understanding its role, setting up the required environment, and mastering basic syntax. These skills will prepare you for advanced data analytics and pre-processing tasks. 1. Overview of Python for Data Science 2. Setting up the Environment 3. Basic Python Syntax ### 2\. Data Structures and Manipulation ### 3\. Data Analysis Libraries ### 4\. Data Cleaning and Preparation ### 5\. Data Wrangling ### 6\. Exploratory Data Analysis ## Earn and Share Your Certificate ## Meet our top-ranked faculty ### Kaushik Swaroop Consultant Advisory-Transformation-BE, KPMG India ## Amity Online Advantages: Why We're the Right Fit for You ### Learn from Analytics Experts and Industry Veterans Learn from experienced faculty and industry professionals who specialize in data analytics and business forecasting. Our experts help you build strong analytical skills and knowledge that meet industry standards. ### Real-World Case Studies and Data-Driven Projects Gain hands-on experience with extracting meaningful insights from raw data that reflect real-world challenges. This practical approach prepares you to make data-driven decisions in any business setting. ### Flexible Learning for Busy Professionals Study at your own pace with a flexible curriculum designed to fit around your schedule, making it ideal for working professionals looking to upskill. ### Certification with Industry Recognition Receive a certification in Descriptive Analytics and Data Pre-processing from Amity University Online, respected by employers across multiple sectors. - Total Modules: 6 Gain insight into a topic and learn the fundamentals. - Duration 16 hours - Level: Beginner No prior experience required - Internship Be eligible for internship (paid/unpaid) - Fee: ₹~~21,000~~ ₹13,000 ## Program Overview and Structure ### 1\. Introduction to Python for Data Analytics Develop a strong foundation in Python for data science by understanding its role, setting up the required environment, and mastering basic syntax. These skills will prepare you for advanced data analytics and pre-processing tasks. 1. Overview of Python for Data Science 2. Setting up the Environment 3. Basic Python Syntax ### 2\. Data Structures and Manipulation Learn to master essential Python data structures, including strings, lists, tuples, sets, dictionaries, and arrays. Develop the skills to manipulate and handle these structures effectively, enabling you to manage and organize data efficiently. 1. Strings 2. Lists 3. Tuples 4. Set 5. Dictionaries 6. Arrays ### 3\. Data Analysis Libraries Develop expertise in using NumPy and Pandas, the cornerstone libraries for data analysis in Python. Gain the skills to perform efficient data manipulation, handle complex datasets, and streamline analysis processes, empowering you to work confidently with structured and unstructured data. 1. NumPy 2. Pandas ### 4\. Data Cleaning and Preparation Master the essential techniques of handling missing values, performing data transformations, engineering impactful features, and inspecting datasets thoroughly. These skills ensure that your data is clean, well-structured, and ready for accurate analysis, laying the foundation for deriving meaningful insights. 1. Handling Missing Values 2. Data Transformation 3. Feature Engineering 4. DecisiData Inspection ### 5\. Data Wrangling Master techniques for joining, reshaping, performing group operations, and aggregating data, which are crucial for organizing and summarizing data effectively. 1. Join 2. Reshaping 3. Group Operations 4. Data Aggregation ### 6\. Exploratory Data Analysis Master univariate, bivariate, and multivariate analysis, along with statistical techniques, to uncover patterns and derive actionable insights from data. 1. Univariate, Bivariate, and Multivariate Analysis 2. Statistical Analysis ## Frequently Asked Questions ### What makes these certifications unique? These certifications are unique because they focus on practical, Python-based approaches to descriptive analytics and data pre-processing, equipping you with industry-relevant skills through real-world examples and hands-on learning. ### Who is this program for? This program is for students, working professionals, and aspiring data analysts who want to build foundational skills in descriptive analytics and data pre-processing using Python to enhance their careers in data-driven roles. ### What are the prerequisites for enrollment? There are no strict prerequisites for enrollment, but a basic understanding of mathematics, statistics, and an interest in Python programming and data analysis would be preferred. ### What tools and technologies will I learn? You will learn Python programming along with key libraries and tools for descriptive analytics and data pre-processing, such as Pandas, NumPy, and data visualization techniques. ### How is the program structured? The program is structured to teach you the fundamentals of descriptive analytics and data pre-processing using Python through a blend of video lectures, practical exercises, and real-world case studies, enabling hands-on learning and skill application. ### Will I receive a certificate upon completion? Yes, students will receive a certification upon successfully completing the program. ### How can I apply what I learn to my career? You can apply what you learn by using descriptive analytics and data pre-processing techniques to clean, organize, and analyze data effectively, strengthening your skills for roles in data analysis, business intelligence, and data-driven decision-making. ### Does this program offer a paid internship? Yes! Students who successfully complete the program may become eligible for a paid internship with KPMG or its associates, depending on selection criteria. ### What roles are available in the paid internship? Interns work in consulting, analytics, product development, and business intelligence, handling dashboard development, data analysis, and strategic problem-solving. ### How much is the stipend? The average internship stipend is ₹8,000 per month. ### Where are the paid internships conducted? Paid internships are conducted in-person at KPMG India offices in cities such as: Gurugram, Noida, Bangalore, Mumbai, Pune, Chennai, Kochi, Kolkata, Chandigarh, and Ahmedabad. ### When do paid internships start? Paid internships are offered quarterly, with the selection process taking place in the last week of each quarter. ### Can I reapply if I don’t get selected? Yes, students can reapply twice, but only in alternate quarters. If a student declines a paid internship after selection, they will not be eligible to reapply. ### How do I enroll and what are the payment options? You can enroll by visiting our website and following the enrollment instructions. We offer various payment options, including credit/debit cards, online banking, and installment plans. ### Can I access course materials after completion? Yes, students will have continued access to learning materials even after completing the course.