Introduction

The course on Data Science with Python and SQL is essential in today’s data-driven world, as it equips individuals with the key skills to analyse, interpret, and extract insights from large datasets. Python, with its powerful libraries such as Pandas, NumPy, and Scikit-learn, enables efficient data manipulation, statistical analysis, and machine learning, while SQL provides the foundation for managing, querying, and extracting data from relational databases. This combination not only allows students to handle real-world data but also helps them make data-driven decisions, solve complex problems, and automate processes in fields like business, finance, healthcare, and technology. Mastering both tools opens doors to a wide range of career opportunities and is fundamental for anyone looking to succeed in the rapidly evolving tech landscape.

Prerequisite:
This course begins at a foundational level and builds up to real-world applications, designed to accommodate learners from both technical and non-technical backgrounds.

→ Basic computer literacy and logical thinking

→ Curiosity and a problem-solving mindset

→ No prior programming or database experience required (course starts from the ground up)

SQA Framework:
This course is aligned with the Professional Development Award (PDA) in Data Science, accredited by the Scottish Qualifications Authority (SQA) at SCQF Level 8. Learners who successfully pass all relevant examinations will be awarded 32 SCQF credits.

Course Objectives:

• Python fundamentals
• Data Wrangling with Python Libraries
• SQL fundamentals including database managements
• Merging Python knowledge and SQL knowledge
• Python transformation

For full details, please submit your inquiry via email.

Hands-on Experience:
The course is delivered with a hands-on approach, featuring practical exercises, lab sessions, and clear, easy-to-understand lessons. It is designed to equip trainees with the essential knowledge and practical skills needed to become proficient Data Scientists using Python and SQL.

Why should you attend this course?

1. If you’re eager to explore the field of Data Science using Python and SQL.
2. If you’ve recently started experimenting with Data Science tools, or have been working with Python and SQL on your own.
3. If your goal is to become a professional Data Scientist.
4. If you’re looking to strengthen and refine your Data Science skills specifically in Python and SQL.
5. If you aim to build a solid foundation in Data Science and advance your career, this course offers a clear and structured path forward.
6. There is a growing global demand for trained and certified Data Scientists proficient in Python and SQL.
7. More professionals than ever before are becoming certified Data Scientists to stay competitive in today’s data-driven job market.

Classes 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.

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 Audience:

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

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.