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Premium Career Track - Advanced Data Engineering & Architecture

Master modern data pipelines, big data platforms, and architectural design to lead enterprise-scale data infrastructure and innovation.
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Course Duration: 200 Hours
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The Premium Career Track – Advanced Data Engineering & Architecture is a high-impact program designed to prepare professionals for expert-level roles in data engineering and architectural leadership. It offers a hands-on, in-depth journey through the tools, technologies, patterns, and methodologies essential for designing, building, and maintaining robust, scalable, and secure data ecosystems.
 
As data becomes the backbone of every digital enterprise, organizations are seeking highly skilled data professionals who can do more than write code—they must design data platforms, enforce governance, optimize pipelines, and collaborate across cloud, dev, and analytics teams. This course goes far beyond traditional data engineering by integrating core data architecture principles, cloud data platform strategy, and modern engineering practices.
 
How to Use This Course
 
The course is structured into thematic modules that begin with foundational concepts and gradually advance to real-world architecture and enterprise implementation. Learners will work on capstone projects, hands-on labs, and architectural blueprints throughout the course.
  • Follow the Learning Path: The program is designed progressively—starting with core engineering skills, moving to platform engineering, then to architectural design and implementation.
  • Gain Real-World Experience: Build pipelines, model data warehouses, implement Lakehouse architecture, and optimize distributed data systems using leading tools like Apache Spark, Kafka, Airflow, dbt, Snowflake, Azure Synapse, and more.
  • Architect for Scale and Governance: Learn how to enforce data quality, scalability, lineage, and cost-efficiency in multi-cloud environments.
  • Apply Frameworks and Best Practices: Each module includes architectural diagrams, design templates, and review checklists to apply directly to enterprise contexts.
  • Bridge Strategy with Execution: The course teaches you not only how to implement systems but also how to evaluate trade-offs, manage technical debt, and lead teams through data modernization.
By the end of this course, you will be equipped to lead data engineering initiatives, influence data strategy, and architect scalable systems that power analytics, AI, and real-time business intelligence across your organization.

Course/Topic 1 - Course access through Google Drive

  • Google Drive

    • 01:20

  • Google Drive

    • 01:20

Course/Topic 2 - Python Programming - all lectures

  • In this lecture session we learn about introduction to python programming for beginners and also talk about features of python programming.

    • 10:21

  • In this lecture session we learn about basic elements of python in python programming and also talk about features of elements of python.

    • 19:37

  • In this lecture session we learn about installation of python in your system and also talk about the best way of installation of python for beginners.

    • 13:18

  • In this lecture session we learn about input and output statements in python programming and also talk about features of input and output statements.

    • 24:05

  • In this lecture session we learn about data types in python programming and also talk about all the data types in python programming.

    • 23:05

  • In this lecture session we learn about operators in python and also talk about how we use operators in python programming.

    • 47:07

  • In this lecture session we learn about different types of operators in python programming and also talk about features of operators in python.

    • 29:47

  • In this lecture session we learn about type conversion in python programming and also talk about features of type conversion in python.

    • 23:39

  • In this lecture session we learn about basic programming in python programming for beginners.

    • 15:56

  • In this lecture session we learn about features of basic programming in python and also talk about the importance of programming in python.

    • 05:13

  • In this lecture session we learn about math modules in python programming and also talk about features of math modules in python.

    • 26:43

  • In this lecture session we learn about conditional statements in python and also talk about conditional statements in python programming.

    • 28:24

  • In this lecture session we talk about basic examples of conditional statements in python.

    • 19:27

  • In this lecture session we learn about greater and less then conditional statements in python programming.

    • 13:39

  • In this lecture session we learn about nested IF Else statements and also talk about features of nested IF else statements.

    • 11:04

  • In this lecture session we learn about looping in python in programming for beginners and also talk about looping in python.

    • 25:06

  • In this lecture session we learn about break and continue keywords and also talk about features of break continue keywords.

    • 20:48

  • In this lecture session we learn about prime number programs in python and also talk about functions of prime number programs in python.

    • 17:31

  • In this lecture session we learn about while loop in python programming and also talk about features of while loop in python.

    • 35:35

  • In this lecture session we learn about nested For loop in python programming and also talk about features of nested For loop.

    • 12:34

  • In this lecture session we learn about features of nested for loop in python and also talk about the importance of nested For loop in python.

    • 12:49

  • In this lecture session we learn about functions in python and also talk about different types of functions in pythons.

    • 19:28

  • In this lecture session we learn about passing arguments to functions in python programming and also talk about features of passing arguments to functions

    • 08:59

  • In this lecture session we learn about return keywords in python and also talk about features of return keywords in python.

    • 12:16

  • In this lecture session we learn about calling a function in python programming and also talk about calling a function.

    • 15:07

  • In this lecture session we learn about factors of calling a function in python programming and also talk about features of calling a function.

    • 20:17

  • In this lecture session we learn about a program to swap 2 numbers using calling a function in python programming.

    • 19:27

  • In this lecture session we learn about functions of arbitrary arguments in python programming and also talk about features of arbitrary arguments.

    • 10:34

  • In this lecture session we learn about functions keywords arguments in python programming and also talk about features of keyword arguments.

    • 06:55

  • In this lecture session we learn about functions default arguments in python programming and also talk about features of default argument.

    • 06:57

  • In this lecture session we learn about global and local variables in python programming and also talk about features of global and local variables.

    • 19:37

  • In this lecture session we learn about global and local keywords and also talk about features of global and local keywords.

    • 10:44

  • In this lecture session we learn about strings in python programming and also talk about features of string in python.

    • 17:42

  • In this lecture session we learn about string methods in python programming and also talk about features of string methods in python.

    • 21:53

  • In this lecture session we learn about string functions in python and also talk about features of strings functions in python.

    • 28:02

  • In this lecture session we learn about string indexing in python programming and also talk about features of string indexing in python programming.

    • 13:51

  • In this lecture session we learn about introduction of lists in python programming and also talk about features of introduction to lists.

    • 06:31

  • In this lecture session we learn about basics of lists python programming and also talk about features of basics of lists in python.

    • 33:09

  • In this lecture session we learn about list methods and also talk about features of list method python programming.

    • 32:43

  • In this lecture session we learn about linear search on list and also talk about features of linear search on list in brief.

    • 23:20

  • In this lecture session we learn about the biggest and smallest number of the list and also talk about features of MAX and Min in a list.

    • 14:40

  • In this lecture session we learn about the difference between 2 lists in python programming and also talk about features of 2 lists.

    • 13:22

  • In this lecture session we learn about tuples in python programming and also talk about tuples in python programming.

    • 20:19

  • In this lecture session we learn about introduction to sets in python and also talk about functions of introduction to sets in python.

    • 32:43

  • In this lecture session we learn about set operations in python programming and also talk about features of set operation in brief.

    • 26:56

  • In this lecture session we learn about set examples and also talk about features set examples.

    • 11:05

  • In this lecture session we learn about introduction to dictionaries in python programming and also talk about featured dictionaries.

    • 14:47

  • In this lecture session we learn about creating and updating dictionaries in python programming and also talk about features of creating and updating dictionaries.

    • 32:49

  • In this lecture session we learn about deleting items in a dictionary in python programming and also talk about features of deleting items in a dictionary.

    • 08:06

  • In this lecture session we learn about values and items in a dictionary in python programming and also talk about features of values and items in the dictionary.

    • 13:14

  • In this lecture session we learn about dictionary methods in python programming and also talk about features of dictionary methods.

    • 18:46

  • In this lecture session we learn about built in methods in python programming and also talk about features of built in methods in python.

    • 20:25

  • In this lecture session we learn about lambda functions and also talk about features of lambda function in python programming.

    • 15:29

  • In this lecture session we learn about file handling in python programming and also also talk about the importance of file handling in python.

    • 15:58

  • In this lecture session we learn about file handling in python programming and also talk about features of file handling in python.

    • 36:13

  • In this lecture session we learn about exception handling in python and also talk about features of exception handling in python.

    • 08:46

  • In this lecture session we learn about exception handling examples in python programming.

    • 25:04

  • In this lecture session we learn about python programs in python programming and also talk about features of python programs

    • 18:40

  • In this lecture session we learn about the program of printing odd numbers in python programming and also talk about the best way of printing.

    • 10:46

  • In this lecture session we learn about counting the number of vowels and consonants in a string and also talk about features of these programs.

    • 21:38

  • In this lecture session we learn about python programs of swapping two numbers in a list by taking indexes as parameters.

    • 14:08

  • In this lecture session we learn about bubble sort and also talk about features of bubble sort in brief.

    • 35:36

  • In this lecture session we learn about operator precedence in python and also talk about features of operator precedence in python.

    • 14:51

  • In this lecture session we learn about operator precedence in python and also talk about features of operator precedence types.

    • 11:28

  • In this lecture session we learn about recursion in python and also talk about features of recursion in python.

    • 22:15

  • In this lecture session we learn about binary search in python and also talk about features of binary search in python programming.

    • 23:18

  • In this lecture session we learn about binary search in python and also talk about the importance of binary search in python.

    • 35:04

  • In this lecture session we learn about object oriented programming and also talk about features of object oriented programming in brief.

    • 21:52

  • In this lecture session we learn about factors and types of object oriented programming in python programming.

    • 17:41

  • In this lecture session we learn about OOPS and procedural programming and also talk about features of OOPS and procedural programming in OOPS.

    • 06:36

  • In this lecture session we learn about OOPS programs in python and also talk about the importance of OOPS.

    • 27:50

  • In this lecture session we learn about inheritance in python programming and also talk about features of inheritance.

    • 37:24

  • In these lecture sessions we learn about features of object creation in python programming and also talk about object creation in python.

    • 24:10

  • In this lecture session we learn about OOPS terminology and functions and also talk about features of OOPS terminology and functions.

    • 24:41

  • In this lecture session we learn about built in class attributes and garbage collection in python programming.

    • 27:26

  • In this lecture session we learn about inheritance in python and also talk about features of inheritance in python.

    • 19:02

  • In this lecture session we learn about the importance of inheritance in python programming and also talk about functions of inheritance.

    • 29:26

  • In this lecture session we learn about programs in inheritance in python programming and also talk about features of inheritance in python.

    • 31:43

  • In this lecture session we learn about polymorphism in python programming polymorphism and also talk about polymorphism in python.

    • 24:47

  • In this lecture session we learn about features of polymorphism in python and also talk about the importance of polymorphism in python.

    • 14:01

  • In this lecture session we learn about the time module in python and also talk about features time module in python in features.

    • 36:22

  • In this lecture session we learn about the importance of time modules in python time module in python in brief.

    • 44:51

  • In this lecture session we learn about the calendar module in python programming in brief.

    • 32:04

  • In these lecture sessions we learn about calendar methods in python programming and also talk about the importance of calendar methods.

    • 37:03

  • Class 28.1 - Boolean in Python

    • 09:32

  • In this lecture session we learn about python iterators and also talk about features of python iterators in brief.

    • 09:30

  • In this lecture session we learn about python programs and summary in python programming and also talk about python programs.

    • 46:37

  • In this lecture sessions we learn about python programs and also talk about features of python programs and summary.

    • 23:27
Course Objectives Back to Top
By the end of this course, learners will be able to:
 
  1. Design scalable and secure data architectures using modern design patterns.
  2. Build real-time and batch ETL pipelines using tools like Apache Airflow, Spark, Kafka, and dbt.
  3. Implement Lakehouse, Data Mesh, and Data Fabric architectural paradigms.
  4. Integrate data systems across cloud platforms (AWS, Azure, GCP).
  5. Enforce data quality, lineage, observability, and governance.
  6. Use columnar storage, partitioning, and indexing to optimize performance.
  7. Create and maintain data warehouses and data lakes using tools like Snowflake, BigQuery, and Redshift.
  8. Apply CI/CD, containerization, and orchestration to data workflows.
  9. Align data architecture with business requirements, compliance, and cost goals.
  10. Lead teams and technical decisions in enterprise data modernization efforts.
Course Syllabus Back to Top
Course Syllabus
 
Module 1: Foundations of Data Engineering
  • Role of a Data Engineer vs. Data Architect
  • Data Engineering Lifecycle and Skills
  • Structured, Semi-Structured, and Unstructured Data
Module 2: Data Modeling & Storage Design
  • Star Schema, Snowflake Schema, Data Vault
  • OLTP vs. OLAP Design Patterns
  • Columnar Storage, Indexing, and Partitioning
Module 3: Data Pipeline Development
  • Batch vs. Real-time ETL/ELT
  • Apache Airflow DAGs and Orchestration
  • Kafka Streaming and Event-Driven Architecture
  • dbt for Transformation Workflows
Module 4: Big Data Processing Frameworks
  • Apache Spark Internals and Optimizations
  • PySpark for Distributed Processing
  • DataFrames vs. RDDs
  • Spark on Databricks and AWS EMR
Module 5: Cloud Data Platforms
  • AWS Glue, Redshift, Athena
  • Google BigQuery and Dataflow
  • Azure Synapse Analytics and Data Factory
  • Data Ingestion with Snowpipe and CDC Tools
Module 6: Data Lakehouse and Modern Architecture
  • Delta Lake, Apache Hudi, Iceberg
  • Lakehouse vs. Data Warehouse Comparison
  • Building Hybrid Lakehouse Architectures
  • Data Mesh and Domain-Driven Design
Module 7: Data Governance, Quality & Security
  • Data Cataloging and Lineage (e.g., Apache Atlas)
  • Great Expectations for Data Quality
  • Role-Based Access and Encryption Best Practices
  • Metadata Management
Module 8: CI/CD and DevOps for Data Engineering
  • GitOps, Jenkins, and CI Pipelines
  • Dockerizing Data Workflows
  • Kubernetes and Airflow on K8s
  • Terraform for Infra as Code
Module 9: Observability and Monitoring
  • DataOps Monitoring Tools
  • Logging, Metrics, and Alerting for Pipelines
  • Cost Optimization and Resource Monitoring
Module 10: Advanced Architecture & Case Studies
  • Building Scalable ML Feature Stores
  • Multi-Tenant Data Systems
  • Case Studies from Netflix, Uber, Airbnb
  • Designing for SLA, Throughput, and Latency
Module 11: Capstone Project
 
  • Design an End-to-End Scalable Data Platform
  • Architecture Review and Cost Analysis
  • Presentation and Peer Feedback
Certification Back to Top

Upon successful completion of the course, learners will receive the Uplatz Certificate of Mastery in Advanced Data Engineering & Architecture. This elite credential validates your ability to design and implement advanced data systems that meet modern scalability, performance, governance, and business intelligence requirements. The certificate represents a deep understanding of both theoretical concepts and practical implementations in cloud, distributed computing, and data modeling. Employers will recognize your readiness to take on strategic roles such as Data Engineering Lead, Senior Data Architect, or Cloud Data Platform Owner. This certification can also enhance your profile when pursuing further qualifications like Google Cloud Data Engineer, AWS Data Analytics Specialty, Databricks Certified Professional, or Microsoft Azure Data Engineer Associate. Whether you're upgrading your role or changing careers, this certification provides a strong signal of your technical leadership in data infrastructure.

Career & Jobs Back to Top
The demand for advanced data engineers and architects has surged globally due to the rise in data-driven decision-making, machine learning, and digital transformation. Enterprises require specialists who can not only build pipelines but also architect scalable data ecosystems that support AI, compliance, real-time analytics, and growth.
 
Graduates of this Premium Career Track – Advanced Data Engineering & Architecture course can pursue leadership roles such as:
  • Senior Data Engineer
  • Lead Data Architect
  • Cloud Data Platform Engineer
  • Big Data Solutions Architect
  • Enterprise Data Strategist
  • ML/AI Infrastructure Engineer
  • DataOps Manager
  • Principal Data Engineer
These professionals are critical in organizations ranging from tech giants and unicorn startups to finance, healthcare, and manufacturing companies. Mastery in data architecture unlocks career opportunities in cloud-native transformations, AI product teams, and enterprise-scale business intelligence programs.
 
Salaries for advanced roles in data engineering and architecture often exceed six figures globally and offer strategic influence over product, analytics, and engineering functions. Freelance and consulting opportunities also abound, with many organizations seeking contract-based experts to audit, optimize, and scale their existing systems.
 
This course provides not only a career pathway but a leadership foundation for professionals looking to drive innovation and operational excellence through data.
Interview Questions Back to Top
  1. What’s the difference between a Data Engineer and a Data Architect?
    A Data Engineer focuses on building pipelines and infrastructure, while a Data Architect designs the overall structure, governance, and integration of data systems.
  2. What is a Lakehouse and how does it differ from a traditional Data Warehouse?
    A Lakehouse combines the scalability of data lakes with the performance and structure of warehouses using formats like Delta Lake and Iceberg.
  3. How do you handle schema evolution in large data platforms?
    By using schema registries, versioning, and supporting backward and forward compatibility through tools like Avro or Delta.
  4. Explain the role of Apache Airflow in data engineering.
    Airflow is an orchestration tool that schedules, monitors, and manages complex workflows via DAGs.
  5. What are key performance optimization techniques in Apache Spark?
    Techniques include using DataFrames over RDDs, caching, partitioning, tuning shuffle partitions, and leveraging broadcast joins.
  6. How would you enforce data quality in pipelines?
    With automated testing frameworks like Great Expectations and by implementing validation at both source and sink stages.
  7. What is the CAP theorem and its relevance in data architecture?
    It states that in distributed systems, only two of Consistency, Availability, and Partition Tolerance can be fully achieved simultaneously.
  8. How do you ensure cost-efficiency in cloud data platforms?
    Through autoscaling, proper partitioning, right-sizing instances, lifecycle policies, and usage tracking with billing dashboards.
  9. Describe an architecture for real-time streaming analytics.
    Use Kafka for ingestion, Spark Streaming for processing, Delta Lake for storage, and a BI tool like Power BI or Superset for visualization.
  10. How do you choose between batch and stream processing?
    Use stream processing for low-latency use cases like fraud detection, and batch for large-scale historical data loads or nightly aggregation.
Course Quiz Back to Top
Start Quiz
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. Can I get help from a tutor if I have doubts while learning from a video course?
A21. Tutor support is not available for our video course. If you believe you require assistance from a tutor, we recommend considering our live class option. Please contact our team for the most up-to-date availability. The pricing for live classes typically begins at USD 999 and may vary.
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