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Data Science Machine Learning with Python Programming

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Introduction

This Data Science and Machine Learning course is quite comprehensive and suitable for you even if you have little knowledge about data science or if you are just exploring.

The course will provide you with all essential materials such problem solving skills, Investigative skills, Innovative skills, observative skills and critical Thinking skills.

You will be learning the latest tools and technologies that are used in large companies such as Google, Netflix, Facebook, and other Retailers.

Prerequisites

Not Required.

SQA Framework:

This course is aligned with the PDA (Professional Development Award) Data Science (SQA) @ SCQF level 8, learners will be able to earn 40 credits upon passing all relevant exams successfully.

Course Objectives:

  1. Introduction to Data Science
  2. Python Basics
  3. Python Advance
  4. Python Advance and Practice Sessions
  5. Basics of Statistics
  6. Data Visualization in Python
  7. Linear Regression
  8. Logistic Regression
  9. Classification using Decision Tree
  10. Unsupervised learning
  11. Basics of NLP
  12. Advanced Regression
  13. Introduction to Neural Networks
  14. Model selection and General ML Techniques
  15. Revision
  16. Project

Hands on Experience:

The features of the course include practical exercises and labs and easy to understand lessons. This course is adequate to provide trainees with the required knowledge and practical skills to be a Data Scientist or AI Engineer.

Why should you attend the course?

  1. If you are curious about Data Science and Machine Learning.
  2. If you have been lately exploring Data Science and Machine Learning or have been playing around with it for a while.
  3. If you want to work as a Professional Data Scientist or an AI Engineer.
  4. If you want to boost your Data Science skills.
  5. Trained and certified Data Scientist are needed worldwide.
  6. More Data Scientist are getting certified than ever before because certifications
  7. Validate your knowledge and skills
  8. Help you remain competitive and employable
  9. Give you job proficiency more quickly
  10. Show dedication to your career

Class Duration:

This is a 16-week course that provides the required knowledge and skills required to become data Scientist.

Learning Modes:

ITPT is currently providing different method of learning opportunities to students. Many people are looking for learning diversity to enhance their qualifications, but they don’t have the time to take on full-time instructor led study or attending courses regularly at their appropriate venues.

     Modes of Course Delivery      Modes of Attendance
    1. Face to Face – Tutor Led learning     1. Weekends
    2. Virtual – Tutor Led learning     2. Weekdays
    3. Blended learning     3. Part time
    4. ELearning     4. Day Release

Job Roles & Opportunities:

Upon completion of related certification exams, you will be able to fit-in the job roles such as:

  1. Data Analyst
  2. Data Engineers
  3. Database Administrator
  4. Data Scientist
  5. Data Architect
  6. Statistician
  7. Business Analyst
  8. Data and Analytics Manager/Project

Our Courses & Training Classes Suit the following:

Target Audiences:

This course covers the knowledge and understanding associated with the SQA PDA data science qualification and will be attractive to learners who are looking for employment at an entry-level position or higher. It would also be suitable for those wishing to prepare for career advancement in their organisation.

The IT training classes which we are currently offering are suitable for a wide range
of candidates including:

  1. School leavers
  2. Adult returnees to education
  3. Individuals who intend to leave school and further their career path in a college or equivalent
  4. Individuals who are in employment and wish to enhance their career prospects
  5. Individuals who wish to start a new career in Data Science
  6. Individuals who wants to get promotion at work
  7. Individuals who wants to upgrade in their Data Science skills
  8. Individuals who intend to progress their career after the study of the PDA into further study at HN level
  9. Individuals who wish to study on a part-time day-release mode

Funding Available:

Course Funding: SAAS PTFG: Scottish Awards Agency for Scotland

This course is funded by SAAS part time funding which is available to eligible individuals only;
SAAS General funding eligibility requirement:

  1. You have to be a resident of Scotland
  2. Either employed or unemployed, if working then earning must be less/equals to 25k a year
  3. Have not used the SAAS funding in this Academic Year.

Other criteria:

☑ Students do not need to pay it back as this is a grant not a loan.

☑ This funding is different from the full time funding which can be applied  by someone who previously granted for a degree, postgrad or any other full time studies (HNC/HND) etc. but not in a same session

☑ Part time funding cannot be received on a same session if one is already receiving any part/full time funding for other courses.

☑ Part Time funding can only be used for one course per academic year

☑ SAAS part time funding academic year starts from Aug to July.

For more information please visit the below link 

www.saas.gov.uk/_forms/funding_guide.pdf

To check your eligibility:

Please follow the below link to check if you qualify for the course funding;

www.saas.gov.uk/part-time/undergraduate-funding

2: Data Lab

Data Skill for Work – About Us

Please follow the above link for more details.

Self Funding

If you do not qualify for SAAS part-time or Data Lab funding, you have the option to self-fund the course.

Fees are payable in advance at the start of the course unless otherwise agreed.

We also provide flexible fee installments to help students in paying their fees.

There are a number of other funding opportunities available to UK and EU students to help them to pay for their studies. Contact the college for more details.

    (Which training centre you looking for admission – Edinburgh or Glasgow)

    Course Info
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