Course Description
The PGP in Data Science at Skill Alleyway is an industry-focused
Data Science Course designed for students, graduates, and working
professionals who want to build successful careers in
Data Science, Artificial Intelligence, Machine Learning,
Business Analytics, and Data Analytics. This live online programme
combines academic excellence with practical industry experience, enabling
learners to master modern data technologies through real-world applications.
The programme covers the complete Data Science ecosystem, including
Python Programming for Data Science,
SQL, Statistics,
Machine Learning, Artificial Intelligence, Business Analytics,
Data Visualization, Big Data, and Data Engineering. Learners gain
practical experience by working with industry datasets, solving
business problems, and developing intelligent data-driven solutions.
Unlike traditional Data Science Classes, our
Project Based Learning methodology allows learners
to apply theoretical knowledge through practical assignments,
real business case studies, and capstone projects. Every module
focuses on building job-ready skills while preparing learners for
globally recognised careers in Data Science and Artificial Intelligence.
Throughout the programme, learners receive expert mentorship,
personalised career guidance, interview preparation, resume building,
LinkedIn optimisation, and placement assistance. Upon completion,
you’ll be equipped with the knowledge and confidence to pursue roles
such as Data Scientist, Data Analyst, Machine Learning Engineer,
AI Engineer, Business Analyst, Business Intelligence Analyst,
and Data Engineer.
What You’ll Learn
- Python Programming for Data Science and Artificial Intelligence.
- SQL for database management and business data analysis.
- Statistics and probability for data-driven decision making.
- Data Cleaning, Data Wrangling, and Feature Engineering.
- Exploratory Data Analysis using real-world datasets.
- Business Analytics and Data Analytics techniques.
- Machine Learning algorithms for predictive modelling.
- Artificial Intelligence concepts and intelligent applications.
- Big Data and modern Data Engineering fundamentals.
- Interactive Data Visualization using Power BI and Tableau.
- Industry-focused Data Science Projects.
- Professional portfolio development using GitHub.
- Career development, interview preparation, and placement guidance.
Course Highlights
- Live Online Mentor-Led Training
- Industry-Focused Curriculum
- Project Based Learning
- Hands-on Practical Assignments
- Real Industry Projects
- Expert Industry Mentors
- Python Programming for Data Science
- Machine Learning & Artificial Intelligence
- Business Analytics & Data Analytics
- Big Data & Data Engineering Concepts
- Interactive Dashboard Development
- Power BI & Tableau Training
- Capstone Project
- GitHub Portfolio Development
- Resume Building & LinkedIn Optimisation
- Mock Technical Interviews
- Career Development Sessions
- Placement Assistance
- Industry-Recognised Certificate
- Recorded Sessions for Revision
- Weekend & Evening Batches
Who Should Enrol?
- Students interested in Data Science and Artificial Intelligence.
- Graduates looking for careers in Data Analytics.
- Working professionals planning a career transition.
- Software Developers interested in Machine Learning.
- Business professionals exploring Business Analytics.
- Engineers interested in Big Data and Data Engineering.
- Anyone looking for a professional Data Science Certification Course.
What You’ll Achieve
After successfully completing the PGP in Data Science,
you’ll develop advanced analytical and technical skills to solve
complex business challenges using Data Science, Artificial Intelligence,
and Machine Learning technologies. You’ll graduate with a professional
portfolio and industry-ready expertise that employers value.
- Build advanced Data Science and Machine Learning models.
- Analyse structured and unstructured business data.
- Create interactive dashboards using Power BI and Tableau.
- Develop predictive analytics solutions.
- Apply Artificial Intelligence to real business challenges.
- Work confidently with SQL databases and Python programming.
- Understand Big Data and Data Engineering workflows.
- Complete multiple industry-ready Data Science Projects.
- Build a strong professional portfolio.
- Prepare for Data Scientist, Data Analyst, AI Engineer, Machine Learning Engineer, Business Analyst, and Data Engineer roles.
Curriculum
- 14 Sections
- 89 Lessons
- 28 Weeks
- Course Curriculum
The PGP in Data Science curriculum is designed to build expertise in Data Science, Artificial Intelligence, Machine Learning, Python Programming, SQL, Business Analytics, Big Data, Data Engineering, and Data Visualization through practical learning, industry projects, and mentor-led live online sessions.
0 - Module 1 – Introduction to Data ScienceBegin your journey into Data Science by understanding its core concepts, applications, and business impact. This module introduces the complete data science lifecycle, industry use cases, and career opportunities. It provides the perfect foundation for learners pursuing a professional Data Science Course, Data Science Masters, or Data Science MSc programme.6
- Module 2 – Python Programming for Data ScienceMaster Python programming for Data Science, Artificial Intelligence, and analytics. Learn variables, functions, object-oriented programming, data structures, and Python libraries including NumPy and Pandas. This module develops practical programming skills required for a professional Machine Learning Course, Artificial Intelligence Course, and modern data science careers.9
- Module 3 – SQL & Database ManagementLearn SQL and database management techniques used to organise, retrieve, and analyse business data efficiently. Topics include SQL queries, joins, indexing, database design, optimization, and data modelling. This module provides practical expertise expected from a professional SQL Course, Data Analytics Course, and Data Science Course.7
- Module 4 – Statistics & ProbabilityDevelop the statistical knowledge required for predictive analytics and machine learning. Learn descriptive statistics, probability, hypothesis testing, regression, and statistical modelling techniques that support intelligent decision-making. This module strengthens the mathematical foundation required for Data Science, Artificial Intelligence, and Machine Learning.7
- Module 5 – Data Analysis with PythonLearn to analyse, clean, transform, and prepare datasets using Python libraries such as Pandas, NumPy, and SciPy. Through practical exercises, learners develop hands-on experience in exploratory data analysis, feature engineering, and reporting, building the practical skills expected from a professional Data Analyst Course and Data Analytics Certification.7
- Module 6 – Data VisualizationConvert complex datasets into meaningful visual insights using Matplotlib, Seaborn, Plotly, and Power BI. Learn dashboard creation, interactive reporting, storytelling with data, and business intelligence techniques. This module strengthens practical skills gained through a Power BI Course and professional Data Analytics Course.7
- Module 7 – Machine LearningExplore supervised learning, unsupervised learning, predictive modelling, feature engineering, model evaluation, and machine learning algorithms using Scikit-learn. Practical projects help learners understand how Machine Learning powers modern Artificial Intelligence while preparing for AI Certification and advanced analytics careers.10
- Module 8 – Artificial IntelligenceDiscover how Artificial Intelligence enhances data science through intelligent automation, predictive analytics, computer vision, recommendation systems, and natural language processing. This module provides practical knowledge aligned with an Artificial Intelligence Course UK and strengthens learners' AI implementation skills across multiple industries.6
- Module 9 – Business AnalyticsLearn how organisations use Business Analytics to improve performance, forecast trends, and support strategic decision-making. Explore KPI reporting, customer analytics, predictive modelling, financial analysis, and executive dashboards using SQL and Power BI, strengthening practical Data Analytics Course knowledge.8
- Module 10 – Big Data & Data EngineeringUnderstand how modern organisations process and manage large-scale datasets using Hadoop, Apache Spark, cloud storage, ETL pipelines, and distributed computing technologies. This module prepares learners for enterprise Data Science, Data Engineering, and advanced Data Science Masters environments.7
- Module 11 – Industry ProjectsApply your knowledge through practical industry projects involving predictive analytics, recommendation systems, fraud detection, customer segmentation, business intelligence, and machine learning applications. These portfolio-ready projects prepare learners for Data Science Jobs UK, Data Science Jobs London, and professional analytics roles.7
- Module 12 – Career Development & Placement SupportPrepare for successful careers in Data Science with CV writing, LinkedIn optimisation, GitHub portfolio development, interview preparation, mock interviews, and career coaching. This module supports learners pursuing Data Science Jobs UK, Data Science Degree opportunities, and careers in Artificial Intelligence and analytics.8
- Capstone ProjectComplete a comprehensive capstone project by applying Data Science, Artificial Intelligence, Machine Learning, SQL, data visualisation, and business analytics techniques to solve a real-world business challenge. This project demonstrates your practical expertise, strengthens your professional portfolio, and prepares you for AI Certification, Data Analytics Certification, and high-demand data science roles across the UK.0
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