Data Engineering Certification

Program Brochure Start Date: August 21st, 2021

Applications are welcomed from all across Pakistan

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Data Engineering Certification Data engineering is the process of preparing data for analytics. By all means, this is a more comprehensive activity than data science (as summarized by this image).

Data science involves using the data to derive value or usable insights. Data engineering brings raw data into a format which is suitable for analytics. The analogy is equivalent to preparing the food (data engineering) versus eating it (data science). Specifically, one needs to ingest the raw data, clean it through many different methods, and design different databases schemas (RDBMS or NoSQL) for storing different varieties of raw data, and create data warehouses, data marts and OLAP cubes for executing multi-dimensional business queries, along with managing and monitoring all aforementioned data and control flows through development of ETL and production pipelines. A new dimension of cloud computing has also been added, making it possible for many organizations to execute the above tasks on AWS, Azure or Google Cloud. Therefore, the importance of a data engineering certification can hardly be underestimated in current times by any type of industry.

This makes FTI’s Data Engineering Certification one of the most powerful, rigorous, and unique certifications of its kind which will teach you all of the aforementioned topics in a hands-on manner.

Why Data Engineering Became So Important?

Managing data is a complicated activity. It is typically carried out by the data team which is part of the IT department in an organization. A couple of decades ago, data management was not difficult. Only a handful of well-known RDBMSs were being used globally (MS SQL Server, Oracle, DB2 and MySQL). The daily data querying and generation size was also small, i.e., from several megabytes to several gigabytes. Data was not that much dirty. Data schema was simple and was easily mapped to an RDBMS. Unstructured data had not been incorporated into RDBMSs and there was no concept of non-relational data stores. BI tools were in their infancy and hence, had limited usage. Bach in those days, it seemed like a small task for any company to run its business operations.

Nowadays, this scenario has overturned. Data is travelling at high velocity (streaming) as well as low velocity (batch). Social network tweets and posts and other non-relational data are now a requirement for marketing analytics and require NoSQL stores. Mergers and

Massive Growth in Unstructured Content

acquisitions are multiplying the amount of data sources and also the dirtiness of the data, hence requiring a more planned data cleaning approach. Data warehousing and OLAP technologies are now an integral part of database design itself. BI tools have become mainstream and have their own requirements for data management before data can be analyzed within them. In fact, the management issues of the IT department have magnified in the face of this scenario, along with the availability of an extensive technology stack to solve these issues.

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Program Features Certification consists of 6 months of live lectures

Classes comprise of 3 hours of interactive lectures, assignments/application projects, discussions, capstone project, and monthly speaker series

Opportunities for collaboration and networking with fellow students both during and after the course

Certificate upon successful completion

How FTI’s Data Engineering Certification benefit you? Learning and honing your SQL Skills at both Basic and

Advanced Level

Theory and hands-on activities with data schema design for both relational and NoSQL databases (particularly Apache Cassandra and MongoDB)

Theory and hands-on activities with data warehouse/ data mart design to solve analytical business needs through querying OLAP cubes. Hands-on will be performed on both on-site and Cloud (AWS)

Theory and hands-on related to the creation of data lakes

Theory and hands-on related to the automating data and control pipelines related to ETL and production

Hands-on with core big data technologies; particularly Apache Spark and Apache Hadoop

Lay a concrete foundation for implementation of data engineering in any organization through a capstone project

Who Should Enroll? Current University Students in 5th to 8th Semester

pursuing Tech/Engineering/CS Degree OR

Fresh Graduates with UP TO 2 years of work experience with relevant background/experience OR

Individuals looking to SWITCH / LAUNCH their career in Data Engineering REGARDLESS of their background

Skills Requirement Beginner-level SQL skills (preferred but not necessary)

Beginner-level Python programming skills (preferred but not necessary)

Knowledge and preferable experience managing any one or more data management tasks (collection, ingestion, storage, transformation, schema design, querying, analysis, visualization, and/or data governance)

Certification Criteria Timely submission of quizzes & assignments.

Timely Submission of Capstone Project report

Project Presentation and Viva

Passing In-class / Take-Home Final Exam

At least 70% attendance in assignments, quizzes and exams

Duration 6 Months (including Course work, Presentations, and

Evaluation)

PKR 24,000/-

15%* EARLY-BIRD DISCOUNT

10% GROUP DISCOUNTS

5% STUDENT REFERRAL DISCOUNTS *FOR APPLICATIONS RECEIVED BEFORE AUGUST 1ST, 2021

TOTAL INVESTMENT

START DATE – AUG 21ST, 2021

CLASS DAYS: SAT – SUN (2 DAYS/ WEEK)

TIMINGS: 5 PM – 8 PM PKT (3 HRS CLASS)

UP TO 8 HOURS OF TEACHING PER WEEK

CLASS SCHEDULE

1+ Month Capstone project

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Course Outline

Module 1 Introduction to Data Engineering Month 1

Module 2 Working with Structured Data, SQL and Relational

Databases Month 2

Module 3 Data Warehouse Concepts, Design & Data Integration Month 3

Module 4 Working with NoSQL Databases Month 4

Module 5 Building and Managing Data Lakes Month 5

Module 6 Building ETL and Data Pipelines Month 6

CAPSTONE PROJECT The capstone project will require participants to implement different facets of a data engineering initiative for

representative organizations (telecommunications, healthcare, agriculture etc.).

Tools & Languages

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A unique feature of our training program is the relentless mentoring and guidance of our extensively academic and industry experienced faculty, who ensure exceptional class interaction and participation through our online teaching medium.

Our Renowned Faculty

Mr. Usman Ali (Academics & Training Director, FTI) is a teaching and analytics professional with 15+ years of experience in teaching and 3+ years of experience in leading a data science team in various research & industry projects. He is a PHD Scholar in Machine Learning from IBA, MS in Computer Science from IBA, and BSc. in Computer Science from University of Peshawar.

Mr. Ahmed Tariq (Data Engineering Instructor, FTI) has been serving as a Senior Data Analyst at 10Pearls. He has outstanding experience of more than 4 years in the field of Business Intelligence and Data Engineering. Mr. Ahmed completed his Bachelors in Computer Science with his Masters in Data Science from FAST NUCES. Prior to 10Pearls, he worked with Systems Limited as a Consultant Data Analyst. He has worked I have worked mostly in the domain of retail, real estate, insurance and infrastructure. Moreover, Mr. Ahmed is a Microsoft Certified Data Analyst.

Mr. Mohammed Ibrahim (Data Engineering Instructor, FTI) With a BS in Computer Science from University of Karachi, Mr. Mohammed Ibrahim used his exceptional Computer Science skills in Business Intelligence, with which companies can get the real-time insights that helps them to lead their business & decision making. Having 4+ years of experience in SQL, data modeling, writing down ETL logics, dashboards designing are his key responsibilities in his current role working as a BI Lead at Retailo Technologies. Previously he was associated with Love for Data (LFD) as a BI Analyst and Atlas Group as a Database Engineer.

Mr. Sohail Imran (Data Engineering Instructor, FTI) has served as an Adjunct Faculty in

numerous reputed universities of Karachi; namely IBA, Usman Institute of Technology, MAJU, and Jinnah University for Women. He is currently pursuing his PhD in Computer Science from PAF KIET, Karachi. In his Research capacity, Mr. Imran Sohail has authored several papers on Big Data, Data Mining, Database Administration, and Cybersecurity. In his professional capacity, he boasts over 10 years of industry experience working in software houses of Karachi. In the past, he has conducted several trainings and workshops for leading organizations of Pakistan in Big Data Analytics. His main areas of strength are in the fields of Big Data Analytics, Data Warehousing, Cloud Computing, and Deep Learning.

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