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Databricks for Cloud Data Engineering

Master Databricks to design scalable data pipelines, robust data engineering, perform advanced analytics, build machine learning models in the cloud.
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Course Duration: 54 Hours
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Databricks for Cloud Data Engineering Online course

The "Databricks for Cloud Data Engineering, Analytics, and Machine Learning" course is a comprehensive, self-paced learning experience designed to empower professionals across the data spectrum with practical, job-ready skills. Whether you're a data engineer, data analyst, or machine learning practitioner, this course provides a powerful foundation for mastering the Databricks Unified Analytics Platform—an industry-leading solution for big data processing, collaborative data science, and scalable machine learning.

Databricks has rapidly become a cornerstone in modern data infrastructure, helping organizations move beyond siloed systems and enabling seamless collaboration across data teams. Built on Apache Spark and tightly integrated with modern cloud services, Databricks allows you to unify your data engineering, data science, and machine learning workflows on a single platform. This course is thoughtfully structured to help you understand, apply, and optimize the core functionalities of Databricks to solve real-world data challenges.

From the very first module, the course immerses you in the Databricks environment through a mix of instructional videos, interactive labs, and practical exercises. You’ll explore the core capabilities of Databricks—such as working with data using Apache Spark and SQL, orchestrating ETL workflows, and developing machine learning models using Python and MLflow. As you progress, you’ll gain hands-on experience in using Databricks notebooks, managing clusters, building robust data pipelines, and tracking experiments efficiently.

What You Will Learn

Instead of abstract theory, the course is grounded in real-world applications. You’ll start by learning how to navigate the Databricks workspace and interact with various components such as notebooks, data lakes, Delta Lake tables, and job clusters. Gradually, you will be introduced to more advanced topics including Spark-based data transformations, performance optimization, and building end-to-end machine learning workflows.

Special attention is given to using SQL and Python—two of the most commonly used languages in data teams—within the Databricks ecosystem. You'll understand how to write scalable code, handle large datasets, and automate pipeline development. By the end of the course, you’ll also be confident in using MLflow, an open-source platform integrated into Databricks, to track experiments, package code, and deploy machine learning models to production environments.

This course goes beyond technical skill-building; it also emphasizes collaboration. In today’s data-driven organizations, success often depends on cross-functional teams working together efficiently. Databricks facilitates this through its collaborative notebook environment, version control, and easy sharing capabilities. Throughout the course, you'll practice how to create shared workflows, review code from team members, and document processes for better transparency and reproducibility.

Who This Course is For

This course is ideal for:

  • Data Engineers looking to build efficient, reliable, and scalable data pipelines.
  • Data Analysts seeking to leverage Spark and SQL for advanced analytics within a cloud-native environment.
  • Machine Learning Practitioners aiming to streamline the model development lifecycle using Databricks and MLflow.
  • Cloud Engineers and Solution Architects interested in understanding how to deploy and optimize analytics workflows in the cloud.
  • Professionals Transitioning to the Cloud from traditional data platforms and looking for a modern, integrated analytics solution.

No matter your current role, if you're involved in data processing, analytics, or machine learning, this course will give you the skills and confidence to work more effectively in Databricks.

How to Use This Course

To get the most out of this course, we recommend following a structured yet flexible learning path. Here's how to effectively use the course material:

  1. Set Clear Goals: Before you begin, determine what you want to achieve from the course. Are you looking to build pipelines, develop ML models, or master Spark with SQL? Setting clear intentions will help you focus on the most relevant sections.
  2. Follow the Suggested Learning Flow: While the course is self-paced, it’s designed in a sequential manner to build upon foundational concepts before moving into more advanced topics. Follow the modules in the recommended order to ensure a smooth learning curve.
  3. Engage with the Interactive Labs: Each module includes guided hands-on labs. These are not optional—they are crucial for internalizing the concepts you learn. Take your time to complete them and experiment beyond the instructions to explore different use cases.
  4. Practice in the Databricks Environment: Whenever possible, use your own Databricks workspace or access a trial environment. Replicating the exercises independently will deepen your understanding and help you troubleshoot real-world issues.
  5. Use Notebooks for Documentation: As you work through examples, make it a habit to document your observations, code, and learnings in Databricks notebooks. This not only reinforces learning but also helps you build a portfolio of work that you can showcase to employers or colleagues.
  6. Leverage Community and Resources: Databricks has a strong online community and extensive documentation. If you get stuck, use forums, GitHub repositories, or the official Databricks documentation to explore additional solutions and best practices.
  7. Revisit and Review: Data platforms evolve quickly. Revisit key sections over time to reinforce your learning, especially when applying the concepts in real projects. The course is designed to be a reference as much as a training tool.
  8. Assess Your Progress: At the end of each major module, reflect on what you’ve learned and try solving a new problem without referring back to the video. This reinforces understanding and helps gauge your readiness to apply the knowledge professionally.
  9. Apply What You Learn to Real Projects: As you gain confidence, start applying what you've learned to actual data problems in your work environment or personal projects. This real-world application bridges the gap between theory and practice.

By the end of this course, you’ll not only understand how to use Databricks effectively, but you’ll also be prepared to lead or contribute to modern data workflows that drive insight, efficiency, and innovation in your organization.

Course Objectives Back to Top

By the end of this course, learners will be able to:

  1. Understand the architecture and capabilities of Databricks and Apache Spark.
  2. Build and orchestrate scalable data pipelines using Delta Lake and Databricks Workflows.
  3. Perform data exploration and analytics using SQL and notebooks.
  4. Implement feature engineering and train machine learning models using MLflow.
  5. Integrate Databricks with cloud storage and BI tools.
  6. Automate data operations with job scheduling and parameterized pipelines.
  7. Ensure data quality, lineage, and governance within the Databricks Lakehouse.
  8. Deploy models in production using Databricks' ML lifecycle management tools.
Course Syllabus Back to Top

Databricks - Course Syllabus

1. Introduction to Databricks

  • Introduction to Databricks
  • What is Databricks? Platform Overview
  • Key Features of Databricks Workspace
  • Databricks Architecture and Components
  • Databricks vs Traditional Data Platforms

2. Getting Started with Databricks

  • Setting Up a Databricks Workspace
  • Databricks Notebook Basics
  • Importing and Organizing Datasets in Databricks
  • Exploring Databricks Clusters
  • Databricks Community Edition: Features and Limitations

3. Data Engineering in Databricks

  • Introduction to ETL in Databricks
  • Using Apache Spark with Databricks
  • Working with Delta Lake in Databricks
  • Incremental Data Loading Using Delta Lake
  • Data Schema Evolution in Databricks

4. Data Analysis with Databricks

  • Running SQL Queries in Databricks
  • Creating and Visualizing Dashboards
  • Optimizing Queries in Databricks SQL
  • Working with Databricks Connect for BI Tools
  • Using the Databricks SQL REST API

5. Machine Learning & Data Science

  • Introduction to Machine Learning with Databricks
  • Feature Engineering in Databricks
  • Building ML Models with Databricks MLFlow
  • Hyperparameter Tuning in Databricks
  • Deploying ML Models with Databricks

6. Integration and APIs

  • Integrating Databricks with Azure Data Factory
  • Connecting Databricks with AWS S3 Buckets
  • Databricks REST API Basics
  • Connecting Power BI with Databricks
  • Integrating Snowflake with Databricks

7. Performance Optimization

  • Understanding Databricks Auto-Scaling
  • Cluster Performance Optimization Techniques
  • Partitioning and Bucketing in Databricks
  • Managing Metadata with Hive Tables in Databricks
  • Cost Optimization in Databricks

8. Security and Compliance

  • Securing Data in Databricks Using Role-Based Access Control (RBAC)
  • Setting Up Secure Connections in Databricks
  • Managing Encryption in Databricks
  • Auditing and Monitoring in Databricks

9. Real-World Applications

  • Real-Time Streaming Analytics with Databricks
  • Data Warehousing Use Cases in Databricks
  • Building Customer Segmentation Models with Databricks
  • Predictive Maintenance Using Databricks
  • IoT Data Analysis in Databricks

10. Advanced Topics in Databricks

  • Using GraphFrames for Graph Processing in Databricks
  • Time Series Analysis with Databricks
  • Data Lineage Tracking in Databricks
  • Building Custom Libraries for Databricks
  • CI/CD Pipelines for Databricks Projects

11. Closing & Best Practices

  • Best Practices for Managing Databricks Projects
Certification Back to Top

Upon successful completion, learners receive a Course Completion Certificate from Uplatz, validating their expertise in Databricks for data engineering, analytics, and machine learning.

This certification is a powerful credential for roles involving modern data architecture, cloud analytics, and AI engineering. It adds significant value to your professional portfolio, especially for those targeting cloud platforms like AWS, Azure, and GCP.

Additionally, this course prepares learners for official Databricks certification exams such as:

  • Databricks Certified Data Engineer Associate
  • Databricks Certified Machine Learning Associate
  • Databricks Lakehouse Fundamentals

Learners gain not only hands-on practice but also the theoretical foundation necessary to pursue these globally recognized certifications.

Career & Jobs Back to Top

By completing this course, you'll open the door to high-demand roles in the cloud data and AI ecosystem, including:

  1. Cloud Data Engineer
  2. Databricks Developer
  3. Data Analytics Engineer
  4. Machine Learning Engineer
  5. Big Data Architect
  6. AI/Data Consultant

Companies across industries—especially those using Azure, AWS, and GCP—are adopting Databricks to modernize their data infrastructure and drive innovation. This course prepares you for success in cloud-first, data-driven environments.

Interview Questions Back to Top

1. What is Databricks and how does it differ from traditional data platforms?
Databricks is a cloud-based data platform that unifies data engineering, analytics, and machine learning. Unlike traditional platforms, it uses Apache Spark for distributed processing and integrates data lakes with data warehouses in a "Lakehouse" architecture, enabling seamless collaboration across teams.

2. How does Delta Lake enhance data reliability and consistency in Databricks?
Delta Lake introduces ACID transactions, schema enforcement, and time travel to cloud storage, ensuring data consistency, version control, and reliability even in complex ETL workflows and streaming use cases.

3. What is the role of MLflow in the Databricks machine learning lifecycle?
MLflow is an open-source platform integrated into Databricks that manages the entire ML lifecycle, including experiment tracking, model packaging, deployment, and the model registry. It promotes reproducibility and scalability of ML workflows.

4. How would you build a data pipeline in Databricks using notebooks and workflows?
You would create modular notebooks for ingestion, transformation, and loading. Then use Databricks Workflows to schedule and orchestrate these notebooks as a pipeline with parameters, conditional logic, and retry policies.

5. What are the advantages of using the Lakehouse architecture over separate data lakes and warehouses?
The Lakehouse architecture combines the scalability of data lakes with the performance and reliability of data warehouses, reducing data duplication, lowering costs, and enabling real-time analytics and machine learning on the same platform.

6. How can Databricks be integrated with BI tools and external data sources?
Databricks supports connectors for Power BI, Tableau, and JDBC/ODBC. It can also integrate with cloud storage (S3, ADLS), relational databases, and REST APIs, making it easy to consume and publish data.

7. What security features does Databricks provide for enterprise data governance?
Databricks offers role-based access control (RBAC), Unity Catalog for fine-grained access, audit logging, encryption at rest and in transit, and compliance with standards like HIPAA, GDPR, and SOC 2.

8. What metrics would you monitor to evaluate the performance of Databricks workloads?
Key metrics include Spark job execution time, cluster utilization, job failure rate, cost per job, data throughput, and task retries. Monitoring tools in Databricks provide detailed execution graphs and logs for performance tuning.

Course Quiz Back to Top
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Q1. What are the payment options? A1. We have multiple payment options: 1) Book your course on our webiste by clicking on Buy this course button on top right of this course page 2) Pay via Invoice using any credit or debit card 3) Pay to our UK or India bank account 4) If your HR or employer is making the payment, then we can send them an invoice to pay. Q2. Will I get certificate? A2. Yes, you will receive course completion certificate from Uplatz confirming that you have completed this course with Uplatz. Once you complete your learning please submit this for to request for your certificate https://training.uplatz.com/certificate-request.php Q3. How long is the course access? A3. All our video courses comes with lifetime access. Once you purchase a video course with Uplatz you have lifetime access to the course i.e. forever. You can access your course any time via our website and/or mobile app and learn at your own convenience. Q4. Are the videos downloadable? A4. Video courses cannot be downloaded, but you have lifetime access to any video course you purchase on our website. You will be able to play the videos on our our website and mobile app. Q5. Do you take exam? Do I need to pass exam? How to book exam? A5. We do not take exam as part of the our training programs whether it is video course or live online class. These courses are professional courses and are offered to upskill and move on in the career ladder. However if there is an associated exam to the subject you are learning with us then you need to contact the relevant examination authority for booking your exam. Q6. Can I get study material with the course? A6. The study material might or might not be available for this course. Please note that though we strive to provide you the best materials but we cannot guarantee the exact study material that is mentioned anywhere within the lecture videos. Please submit study material request using the form https://training.uplatz.com/study-material-request.php Q7. What is your refund policy? A7. Please refer to our Refund policy mentioned on our website, here is the link to Uplatz refund policy https://training.uplatz.com/refund-and-cancellation-policy.php Q8. Do you provide any discounts? A8. We run promotions and discounts from time to time, we suggest you to register on our website so you can receive our emails related to promotions and offers. Q9. What are overview courses? A9. Overview courses are 1-2 hours short to help you decide if you want to go for the full course on that particular subject. Uplatz overview courses are either free or minimally charged such as GBP 1 / USD 2 / EUR 2 / INR 100 Q10. What are individual courses? A10. Individual courses are simply our video courses available on Uplatz website and app across more than 300 technologies. Each course varies in duration from 5 hours uptop 150 hours. Check all our courses here https://training.uplatz.com/online-it-courses.php?search=individual Q11. What are bundle courses? A11. Bundle courses offered by Uplatz are combo of 2 or more video courses. We have Bundle up the similar technologies together in Bundles so offer you better value in pricing and give you an enhaced learning experience. Check all Bundle courses here https://training.uplatz.com/online-it-courses.php?search=bundle Q12. What are Career Path programs? A12. Career Path programs are our comprehensive learning package of video course. These are combined in a way by keeping in mind the career you would like to aim after doing career path program. Career path programs ranges from 100 hours to 600 hours and covers wide variety of courses for you to become an expert on those technologies. Check all Career Path Programs here https://training.uplatz.com/online-it-courses.php?career_path_courses=done Q13. What are Learning Path programs? A13. Learning Path programs are dedicated courses designed by SAP professionals to start and enhance their career in an SAP domain. It covers from basic to advance level of all courses across each business function. These programs are available across SAP finance, SAP Logistics, SAP HR, SAP succcessfactors, SAP Technical, SAP Sales, SAP S/4HANA and many more Check all Learning path here https://training.uplatz.com/online-it-courses.php?learning_path_courses=done Q14. What are Premium Career tracks? A14. Premium Career tracks are programs consisting of video courses that lead to skills required by C-suite executives such as CEO, CTO, CFO, and so on. These programs will help you gain knowledge and acumen to become a senior management executive. Q15. How unlimited subscription works? A15. Uplatz offers 2 types of unlimited subscription, Monthly and Yearly. Our monthly subscription give you unlimited access to our more than 300 video courses with 6000 hours of learning content. The plan renews each month. Minimum committment is for 1 year, you can cancel anytime after 1 year of enrolment. Our yearly subscription gives you unlimited access to our more than 300 video courses with 6000 hours of learning content. The plan renews every year. Minimum committment is for 1 year, you can cancel the plan anytime after 1 year. Check our monthly and yearly subscription here https://training.uplatz.com/online-it-courses.php?search=subscription Q16. Do you provide software access with video course? A16. Software access can be purchased seperately at an additional cost. The cost varies from course to course but is generally in between GBP 20 to GBP 40 per month. Q17. Does your course guarantee a job? A17. Our course is designed to provide you with a solid foundation in the subject and equip you with valuable skills. While the course is a significant step toward your career goals, its important to note that the job market can vary, and some positions might require additional certifications or experience. Remember that the job landscape is constantly evolving. We encourage you to continue learning and stay updated on industry trends even after completing the course. Many successful professionals combine formal education with ongoing self-improvement to excel in their careers. We are here to support you in your journey! Q18. Do you provide placement services? A18. While our course is designed to provide you with a comprehensive understanding of the subject, we currently do not offer placement services as part of the course package. Our main focus is on delivering high-quality education and equipping you with essential skills in this field. However, we understand that finding job opportunities is a crucial aspect of your career journey. We recommend exploring various avenues to enhance your job search: a) Career Counseling: Seek guidance from career counselors who can provide personalized advice and help you tailor your job search strategy. b) Networking: Attend industry events, workshops, and conferences to build connections with professionals in your field. Networking can often lead to job referrals and valuable insights. c) Online Professional Network: Leverage platforms like LinkedIn, a reputable online professional network, to explore job opportunities that resonate with your skills and interests. d) Online Job Platforms: Investigate prominent online job platforms in your region and submit applications for suitable positions considering both your prior experience and the newly acquired knowledge. e.g in UK the major job platforms are Reed, Indeed, CV library, Total Jobs, Linkedin. While we may not offer placement services, we are here to support you in other ways. If you have any questions about the industry, job search strategies, or interview preparation, please dont hesitate to reach out. Remember that taking an active role in your job search process can lead to valuable experiences and opportunities. Q19. How do I enrol in Uplatz video courses? A19. To enroll, click on "Buy This Course," You will see this option at the top of the page. a) Choose your payment method. b) Stripe for any Credit or debit card from anywhere in the world. c) PayPal for payments via PayPal account. d) Choose PayUmoney if you are based in India. e) Start learning: After payment, your course will be added to your profile in the student dashboard under "Video Courses". Q20. How do I access my course after payment? A20. Once you have made the payment on our website, you can access your course by clicking on the "My Courses" option in the main menu or by navigating to your profile, then the student dashboard, and finally selecting "Video Courses". Q21. 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