In this course, participants will learn how to use scientific methods, processes, algorithms, and systems in this interdisciplinary field and get the essential skills expected from a data scientist & ML Engineer.

Through this program, in addition to learning how to build complex quantitative algorithms and synthesize large amounts of information, gain the leadership and communication skills necessary to deliver measurable and tangible results to a variety of business stakeholders!

Program Flow:
- Machine Learning/Deep Learning (8 Weeks)

Program Coverage:
- 75+ Hours In-class Training
- 15+ Hours Mentoring Service
- 30+ Hours Lab/Project Sessions
- 5+ Real World Projects
- 1 Capstone Projects
- CMS (Career Management Service) Support until First Hiring

Targeted Job Titles:
- Data Scientist
- Machine Learning Engineer
- Data (Science) Consultant

Eligibility: Candidates are supposed to have intermediate python programming knowledge and familiarity with fundamental IT issues such as Linux it and SQL Basics. In addition, they are expected to be knowledgeable about how to analyze data with Python (NumPy, pandas, Seabırn, Matplotlib, etc.) and SQL.

Machine Learning/Deep Learning (Premium)

This course is designed for people with previous experience in the IT industry. 

Following the completion of the preparation period, a 14-week DevOps training will begin. The skills you learn in our DevOps Learning Path will enhance your qualifications and open more significant opportunities to significantly leverage your income as a much sought-after professional in the high-demand IT job market.
 
Program Flow:
- DevOps (14 Weeks)

Program Coverage:
- 186 Hours In-class Training
- 26 Hours Mentoring Service
- 54 Hours Lab/Project Sessions
- 40+ Hands-on
- 6 Projects
- 1 Capstone Project
- CMS (Career Management Service) Support until First Hiring

Targeted Job Titles:
- DevOps Engineer
- SysOps Administrator 
- Platform Engineer
- Build Engineer
- Site Reliability Engineer
- Release Manager

Eligibility: Candidates are supposed to have AWS cloud computing knowledge (JSON&YAML, IAM, EC2 (ELB, AS, SG, EBS), Cloudformation, DB, VPC, Route53, Network (IP addressing, subnetting, TCP/IP Model) and familiarity with basic IT issues such as Linux, SDLC, GIT.