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Python for Data Engineering and Machine Learning (Python Institute) Intermediate

The Python for Data Engineering and Machine Learning course by Python Institute equips aspiring data analysts, junior data engineers, and career changers with foundational Python programming and data analysis skills to solve the critical industry challenge of transforming raw data into actionable insights. With over 100,000 Python-related jobs currently unfilled globally, this course delivers job-ready competencies in data collection, cleaning, transformation, and visualization using core Python libraries like NumPy and csv, preparing learners for entry-level roles where proficiency in data ethics and basic statistics is increasingly required.

This course prepares candidates for the PCED™ – Certified Entry-Level Data Analyst with Python certification, validating essential skills recognized by employers in finance, healthcare, and tech. Koenig Solutions enhances readiness with official vendor-authorized courseware and 30-day lab access, ensuring hands-on mastery. Graduates gain a verifiable credential that serves as a career accelerator into associate-level data roles and further certifications like PCAD™.

40 Hours (5 Days)
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3+ professionals trained

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Course Overview

The Python Institute's *Python for Data Engineering and Machine Learning* course is designed to equip learners with the essential skills needed to excel in data-centric roles such as data engineer, machine learning engineer, and data analyst. This comprehensive program prepares candidates for the PCAD™ – Certified Associate Data Analyst with Python certification exam (PCAD-31-02), validating proficiency in Python-based data workflows. With 86% of data scientists using Python as their primary language, demand for these skills continues to surge across finance, healthcare, and technology sectors. The course serves professionals aiming to master the full data lifecycle—from acquisition and cleaning to analysis and insight communication—using industry-standard tools and methodologies.

Students engage with key technologies including Pandas, NumPy, Matplotlib, Seaborn, SQL, and foundational machine learning libraries, all within hands-on lab environments that simulate real-world data challenges. Through practical exercises, learners build complete data analysis pipelines, clean and transform raw datasets, perform statistical analysis, and create interactive visualizations. A capstone project involves analyzing a multi-source dataset to derive actionable business insights, mirroring actual job responsibilities. These labs are conducted in an interactive online environment powered by OpenEDG Testing Service, ensuring students gain applied experience with the same tools used by leading organizations in data engineering and analytics.

By completing *Python for Data Engineering and Machine Learning*, participants are fully prepared for the globally recognized PCAD certification, which holds strong credibility among employers seeking qualified data professionals. Certified individuals can pursue competitive salaries, with Python-related roles averaging $112,577 annually and reaching over $176,000 for specialized positions like machine learning engineer. Koenig Solutions enhances this journey with Guaranteed-to-Run batches and access to official Python Institute courseware, ensuring structured, instructor-led success. Graduates emerge ready to advance into high-growth careers where they can design intelligent data systems and drive data-informed decision-making in modern enterprises.

What You'll Learn

✓Construct ETL pipelines using Pandas and SQLAlchemy to ingest and transform data from diverse sources.
✓Implement robust data workflows using Python exception handling, logging, and modular functions.
✓Perform data wrangling and feature engineering on large datasets using NumPy and Pandas.
✓Develop predictive models and perform statistical analysis using Scikit-Learn and SciPy.
✓Build distributed data processing jobs using PySpark to handle high-volume datasets.
✓Visualize complex analytical findings and model performance metrics using Matplotlib and Seaborn.

Skills You'll Gain

Python Data Analysis Pandas DataFrames NumPy Arrays Matplotlib Visualization Seaborn Plots Python SQL Integration Data Cleaning Statistical Analysis Descriptive Statistics Inferential Statistics Regression Analysis Machine Learning Fundamentals Model Evaluation Data Validation Data Visualization Python for Data Engineering PCEP Certified Entry-Level Python Programmer PCAP Certified Associate in Python Programming

Prerequisites

Recommended knowledge before taking this course
  • To enroll in Python for Data Engineering and Machine Learning, students must meet the following technical prerequisites. Candidates should possess completion of PCAP-31-03 or equivalent 150 hours of Python programming experience. Proficiency in object-oriented programming and intermediate Python syntax is required to develop robust data engineering solutions. Applicants must demonstrate experience with Apache Spark or Dask for managing large-scale data processing. Familiarity with ETL pipeline design patterns and SQL database querying is essential for integrating data from multiple sources. Practical experience using pandas for data manipulation and scikit-learn for building machine learning models is necessary to succeed in this curriculum.
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Certification Exam

Everything you need to know about the Python for Data Engineering and Machine Learning (Python Institute) certification exam

Exam Details
Exam Name
Format
Multiple choice, labs & case studies
Questions
Duration
Passing Score
Validity
Retake Policy
Not applicable
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Python for Data Engineering and Machine Learning (Python Institute)

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Course Curriculum

Structured learning with hands-on labs and real-world scenarios

1
Day 1– Python Programming Essentials (PCAP-31-03 Alignment)
Configuring Python development environments Managing variables, types, and casting Implementing conditional logic and control flow Mastering iterative loops and list comprehensions Building modular functions and scope management Utilizing data structures: lists, tuples, and dictionaries Exception handling and debugging techniques Exam preparation: PCAP-31-03 (Passing score: 70%)
2
Day 2– Data Engineering Foundations with Pandas
Dataframe manipulation with Pandas Importing complex CSV, JSON, and SQL datasets Resolving missing values and data imputation Performing precise type conversion and casting Eliminating redundant duplicate records Standardizing inconsistent data formats Filtering and merging datasets Exporting cleaned datasets for ML pipelines
3
Day 3– Numerical Analysis and Data Exploration
Processing multidimensional arrays via NumPy Calculating essential descriptive statistics Executing complex aggregation operations Conducting exploratory data analysis (EDA) Identifying statistical outlier anomalies Performing deep correlation analysis Vectorized operations for performance Summarizing critical dataset characteristics
4
Day 4– Machine Learning and Pipeline Deployment
Model training with Scikit-Learn Implementing supervised learning algorithms Feature engineering and selection Evaluating model performance metrics Building automated ML pipelines Serializing models for production API consumption for real-time data ingestion SQL integration for data retrieval
5
Day 5– Data Visualization and Professional Reporting
Designing high-impact visuals with Matplotlib Creating interactive plots with Seaborn Interpreting charts with statistical accuracy Selecting optimal chart types for stakeholders Annotating visualizations for clarity Structuring professional technical reports Presenting findings to technical teams Best practices for data storytelling

What's Included in Your Training

Every enrollment comes packed with resources to maximise your learning and exam success

Career Outcomes

78%

of Python for Data Engineering and Machine Learning (Python Institute) certified professionals report career advancement within 6 months

Salary Impact

+22%

Average salary increase reported after obtaining the Python for Data Engineering and Machine Learning (Python Institute) certification

Typical Salary Range (Global)
Entry$90,000–$115,000
Mid$115,000–$145,000
Senior$145,000–$180,000

*Source: Glassdoor / LinkedIn 2025

Job Roles

6
  • Data Analyst
  • Python Data Engineer
  • Machine Learning Associate
  • Data Automation Engineer
  • Associate Data Scientist
  • ETL Developer

Companies Hiring

5,000+
Google Amazon Microsoft Deloitte Accenture IBM Capgemini JPMorgan Chase Wipro Infosys

and 5,000+ organizations worldwide seeking Python for Data Engineering and Machine Learning (Python Institute) certified professionals

Real Transformations

Course Student Reviews

Real results from IT professionals who trained with Koenig — rated 4.9/5 from 18,400+ verified reviews.

18,400+
Verified Reviews
4.9 / 5
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  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

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    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

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    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

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    Head of L&D, UK Enterprise

    100+ Learners Trained ✓ Verified
  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
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    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

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    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

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    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified
  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained ✓ Verified
  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
  • ★★★★★

    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified
  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig's on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained ✓ Verified
  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig's structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert ✓ Verified
  • ★★★★★

    “As an L&D head I've used 5 training vendors. Koenig's MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained ✓ Verified
  • ★★★★★

    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified ✓ Verified
  • ★★★★★

    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified
  • ★★★★★

    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig's corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training ✓ Verified

Frequently Asked Questions

Everything you need to know about the Python for Data Engineering and Machine Learning (Python Institute) training course

Is the certification exam included in the Python for Data Engineering and Machine Learning course, and what is the exam fee if separate?
The Python Institute certification exam is not included in the course fee. Candidates must purchase a PCAD™ exam voucher separately for $195 USD. This voucher remains valid for 12 months and allows exam scheduling via TestNow™. Optional bundles featuring retakes and practice tests are available for additional fees.
What training formats does Koenig offer for Python for Data Engineering and Machine Learning, and is Guaranteed-to-Run scheduling available?
Koenig offers live online 1-on-1, public live, and self-paced Flexi formats for Python for Data Engineering and Machine Learning. All sessions are Guaranteed-to-Run regardless of enrollment numbers. This ensures your training proceeds as scheduled, providing reliable planning for your professional certification preparation journey.
How long is lab access provided for the Python for Data Engineering and Machine Learning course, and what environment is used?
You receive 30 days of post-course lab access via Koenig’s cloud-hosted LET platform. These secure, high-performance virtual machines come pre-configured with Python, Pandas, NumPy, Scikit-Learn, and Jupyter. This environment is optimized for mastering Python for Data Engineering and Machine Learning through intensive, hands-on practice.
What is Koenig's rescheduling and cancellation policy for the Python for Data Engineering and Machine Learning course?
Koenig allows free rescheduling if requested over 10 days before the start date. Changes within 10 days incur a 50% fee. Cancellations made 15 days prior qualify for a full refund. Written notice is required, and these policies apply to all Guaranteed-to-Run Python for Data Engineering and Machine Learning sessions.
What is the format, number of questions, passing score, and time limit for the PCAD™ certification exam?
The PCAD™ certification exam consists of 48 single- and multiple-select questions plus scenario-based items. You have a 60-minute time limit and must achieve a 75% passing score. The exam covers data acquisition, modeling, and visualization, and is delivered via the secure OpenEDG TestNow™ proctoring platform.
How long is the PCAD™ certification valid, and what is the renewal process and cost?
The PCAD™ certification is valid for 6 years from the date of issuance. To renew, you must retake the updated version of the exam before it expires. While there is no continuing education requirement, re-examination incurs the standard $195 USD fee for a new Python Institute exam voucher.
What post-training support does Koenig provide after completing the Python for Data Engineering and Machine Learning course?
Koenig provides 30 days of post-training support, including access to class recordings, curated study materials, and expert mentorship. You also receive personalized exam guidance and are eligible for a complimentary course retake within one year to ensure you fully master Python for Data Engineering and Machine Learning.
What are the prerequisites or recommended experience needed for the Python for Data Engineering and Machine Learning course?
Participants should possess foundational Python programming skills, basic data structure knowledge, and statistical familiarity. We recommend completing entry-level courses like PCEP or having equivalent experience. This ensures you are fully prepared for the advanced data engineering and machine learning concepts taught in this Python Institute program.
What career impact and salary potential does the PCAD™ certification offer for data analysts?
PCAD™ certification holders often secure roles as Data Engineers or Machine Learning Associates, with U.S. salaries ranging from $75,000 to $110,000. This credential validates your practical expertise in Python-based data workflows, significantly enhancing your employability and professional standing within competitive, data-driven sectors worldwide.
How does instructor-led training compare to self-study for preparing for the PCAD™ certification?
Instructor-led training provides structured learning, real-time doubt resolution, and hands-on labs, increasing your first-attempt success rate. Unlike self-study, Koenig’s program includes 40 hours of live instruction and practice tests. This guided approach to Python for Data Engineering and Machine Learning significantly improves your exam readiness compared to independent preparation.

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