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Data Analysis with Python

This course teaches data analysis using Python, including data import, manipulation, visualization, machine learning and predictions. It uses Pandas, Numpy, and Scipy libraries and skills gained include predictive modelling, Python, data analysis and visualization. It can be applied to multiple certification programs.


Per Person




3 Days


Face-to-face (F2F) / Virtual Class


Choose your preference

Customize your training experience by first selecting your preferred Training Delivery Format and then choosing the Class Type that best aligns with your goals and needs.

Public Class

Learn, collaborate and make new friends with similar interest in a shared virtual or physical classroom.

Private Class

Achieve personalized learning in a private setting with your dedicated instructor.

In-House Training

Similar to a private class, but your instructor will deliver the training face-to-face at your preferred venue.


Customize your training to suit specific requirements of your organization for optimal results.


Course structure

Course Overview

Analysing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models.

Topics covered include:

  • collecting and importing data
  • cleaning, preparing & formatting data
  • data frame manipulation – summarizing data,
  • building machine learning regression models
  • model refinement
  • creating data pipelines

You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations.

You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects.

You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions.

Course Objectives

You will learn:

  • Develop Python code for cleaning and preparing data for analysis – including handling missing values, formatting, normalizing, and binning data.
  • Perform exploratory data analysis and apply analytical techniques to real-word datasets using libraries such as Pandas, Numpy and Scipy.
  • Manipulate data using dataframes, summarize data, understand data distribution, perform correlation and create data pipelines.
  • Build and evaluate regression models using machine learning scikit-learn library and use them for prediction and decision making.

Course Prerequisite

You should have a working knowledge of Python and Jupyter Notebooks.

Course Content

Part 1: Importing Datasets

  • The Problem
  • Understanding the Data
  • Python Packages for Data Science
  • Importing and Exporting Data in Python
  • Getting Started Analyzing Data in Python

Part 2: Data Wrangling

  • Pre-processing Data in Python
  • Dealing with Missing Values in Python
  • Data Formatting in Python
  • Data Normalization in Python
  • Binning in Python
  • Turning categorical variables into quantitative variables in Python

Part 3: Exploratory Data Analysis

  • Exploratory Data Analysis
  • Descriptive Statistics
  • GroupBy in Python
  • Correlation
  • Correlation – Statistics
  • Analysis of Variance ANOVA

Part 4: Model Development

  • Model Development
  • Linear Regression and Multiple Linear Regression
  • Model Evaluation using Visualization
  • Polynomial Regression and Pipelines
  • Measures for In-Sample Evaluation
  • Prediction and Decision Making

Part 5: Model Evaluation

  • Model Evaluation and Refinement
  • Overfitting, Underfitting and Model Selection
  • Ridge Regression
  • Grid Search

Who Should Attend

Python is the programming language that opens more doors than any other, and the more you understand Python, the more you can do in the 21st Century. With a solid knowledge of Python, you can work in a multitude of jobs and a multitude of industries.

Data Analysis with Python certification will be particularly valuable for:

  • Aspiring programmers and learners interested in learning programming for fun and job-related tasks;
  • Learners looking to gain fundamental skills and knowledge for an entry-level job role as a software developer, data analyst, or tester;
  • Industry professionals wishing to explore technologies that are connected with Python, or that utilize it as a foundation;
  • Team leaders, product managers, and project managers who want to understand the terminology and processes in the software development cycle to more effectively manage and communicate with production and development teams.

Learn, certify
and secure your job


Per Person




3 Days


Face-to-face (F2F) / Virtual Class


Frequently asked questions

How do I take the PCEP exam?

  1. Read the PCEP Testing Policies and TestNow specifications to make sure you follow the code of conduct, meet all the technical requirements, and know what to expect during your exam session.
  2. Create a Test Candidate account if you haven’t already done it. (Download a PDF Tutorial).
  3. Go to OpenEDG Voucher Store and buy an exam voucher. You can choose between a single-shot voucher, voucher with retake, and voucher + practice test bundle.
  4. Log in to your test candidate account, enter the voucher code, perform a diagnostics check, check in, and launch your exam session. (Download a PDF Tutorial).

Can I retake the exam?

You can only retake a failed exam after 7 days of your last attempt (waiting period).

  • If you purchased a voucher with a free retake option and failed your exam – wait 7 days, go to the Exam History section on your Test Candidate account, and click the Get Free Retake button that will become activated next to your exam session status information. Your exam voucher will automatically be assigned to your account and become available in the Certify section.
  • If you purchased a single-shot voucher and failed your exam, you need to purchase a new voucher to take the exam again. You can launch a new exam session after 7 days from your last attempt.

How do I access the PCEO practice test?

Here’s what you need to do to access the official Python Institute PCEP practice tests:

  1. Go to OpenEDG Voucher Store and buy a practice test voucher. (skip this step if you already have a voucher)
  2. Log in to your OpenEDG Learner Account, click “Practice”, enter the voucher code, read and accept the terms and conditions, and activate the practice test. (Download a PDF Tutorial)

Note that if you’re logged in as Test Candidate, you need to switch your role to Learner in order to be able to launch the practice test.

I passed the PCEP exam. What now?

Congratulations! You’ve officially joined the Python Institute certified community, and earned an industry credential that validates your proficiency in Python, computer programming, and related technologies. Within 24 hours of your exam, you will receive an email with a link to your digital certification, verification code, and a PCEP badge issued by Credly’s Acclaim. You can now share your awesome achievement with your peers, colleagues, and employers via LinkedIn and other social media channels.

What next? Keep on learning, keep on mastering your Python skills, and keep on climbing the certification ladder. Get yourself prepared for the PCAP certification to take your career to an even higher level.