Introduction to Our Learning Path and Package

Learning Path
  1. Our Learning Path is a roadmap to build one’s career in a certain skill proficiency area like Data, Web etc
  2. Objective of a learning path is to train our students on everything a student is expected to know for one or multiple industry roles in that proficiency area.
  3. Student can get engaged with us from as early as Higher Secondary School and we will offer right career counselling advice to choose right proficiency area and build his custom Learning path
Learning Package
  1. Learning Path for a proficiency track is further a collection of Learning Packages which caters to various requirement of our students in different phases of their journey with us.
  2. There are 3 types of Learning Package – Elementary, Foundation and Advanced.
Learning Module
  1. Each Learning Package consists of multiple learning modules or courses which focuses on one subject area.
    The syllabus is designed by industry experts keeping in mind industry requirements.
The picture depicts journey of a student @Alphabetz
Elementary Learning Package

Our Elementary Learning Package is offered to school students or is suitable for students who want to achieve entry level skills for a career in IT.  This Learning Package is common to all Learning Paths.

  • Entry level course focusing on Basic Programming skills.
  • Pre-Requisites: Class XI onwards with Science / Maths background
  • Course Objective: Basic Digital Literacy and entry point to IT Career track
  • Curriculum: Curriculum aligned to CBSE /ISC Computer Science Syllabus.
  • Basic Software Engineering , One Key Language ( Java or Python ) and problem solving skills with ample hands on.
At this moment we are only offering Data Learning Path and their Learning Packages
Introduction to Data Learning Path
Our Data Learning Path has been designed to enable our students to build a career in Data proficiency track and build their skill set to fit industry job opportunities for the following roles:
  1. Data Engineer
  2. Data Analyst
  3. Data Modeler or Database developer
  4. MLOps Engineer

There are two Learning Packages offered under Data Learning Path which are as follows: Data Foundation Package, Data Advanced Learning Package

1. Data Foundation Package

Data Foundation Package is suitable for students who are at the beginning of undergraduate education and are willing to build a skill base over Data Engineering related proficiency skill.  

Pre-Requisites : Entry to Data Foundation Learning Package requires our student to have fulfilled following pre-requisites:
  1. Completed Class XII with Science from any recognized board with minimum 60% marks
  2. Completed Alphabetz Elementary Learning Package or have following knowledge:
    • Entry Level Python Programming skills
    • Have basic Software Engineering knowledge

The list of Learning Modules offered under Data Foundation Learning Package are as follows:

  1. Python Programming Workshop
  2. DBMS concept and ANSI SQL Workshop
  3. Introduction to Data Modelling and Database Design with Workshop
  4. Introduction to Cloud Computing and Distributed system
  5. Introduction to Data Engineering and Big Data processing
  6. Introduction to Data warehousing and Data Lakehouse
  7. Introduction to AI/ML and Data Analytics
  8. Basic concept of Statistics and Mathematical Model
  9. Data Pre-processing and Exploratory Data Analysis (EDA)
  10. Data Visualization and Reporting with Power BI desktop
  • Effort240 – 270 hours
  •  
    Duration 9 months without a break or can be done stepwise over a period of 12 quarters
  •  
    Number of Learning Modules10 and Sandbox Lab
  •  
    Target Industry RolesData Engineer, Data Migrator, Data Modeler or Database developer
  •  
    PriceINR 40,000 (Domestic) and USD $1000 (International) plus all applicable taxes
  •  
    Payment Plan50% during Registration , Rest 50% after 6 months
Download Course Brochure Now
2. Data Advanced Learning Package

Data Advanced Learning Package is suitable for students who are willing to build specialization on Artificial Intelligence / Machine Learning beyond Data Pre-Processing

Pre-Requisites : Entry to Data Advanced Learning Package requires our student to have fulfilled following pre-requisites:
  1. Completing BTech / MTech / MCA / BCA degree
  2. Completed Alphabetz Data Foundation Learning Package

The list of learning Modules offered under Data Advanced Learning Package are as follows:

  1. Introduction to Machine Learning and ML Prediction Algorithms
  2. Evaluation and Model Selection
  3. Introduction to Model Life Cycle Management and MLOps
  4. Introduction to Time Series Forecasting
  5. Introduction to Deep Learning and Neural Networks Architecture
  6. Introduction to Reinforcement Learning
  7. Introduction to Natural Language Processing and Generative AI
  • Effort120 – 150 hours
  • Duration6 months
  • Number of Learning Modules7 and Analytics Assignment on Sandbox Lab
  • Target Industry RolesData Analyst, MLOps Engineer
  • PriceINR 40,000 ( Domestic ) and USD $1000 ( International ) plus all applicable taxes
  • Payment Plan50% during Registration , Rest 50% after 6 months
Download Course Brochure Now
Data Engineering and AI/ML Analytics Sandbox Lab on Azure Stack

This is a cloud based environment where students will have a simulated end to end Data Engineering ecosystem where students will be completing hands on assignments built on industry use cases very similar to what they will be expected to do after joining the industry.

Our Data Engineering Lab

Data Engineering Sandbox Lab built on Microsoft Azure with Azure Tech Stack

A cloud based environment where students will have a simulated end to end Data Engineering ecosystem showcasing journey of data all the way from Ingestion to Reporting.

Students will be completing hands on assignments built on industry use cases very similar to what they will be expected to do after joining the industry.

The picture depicts a Physical Agile Lab where students will have option to come and collaborate with other students to complete assignments following Scrum Methodology.