Data Science & Machine Learning with Python

The UK stands at the epicentre of the global data revolution, with an explosion of opportunities awaiting those skilled in data science and machine learning. Our Data Science & Machine Learning with Python course bridges the gap between raw data and actionable insights. By merging Python's versatility with machine learning prowess, this Data Science & Machine Learning with Python course offers a deep dive into visualising data, deploying real-time predictions, mastering algorithms, and much more. As industries recognise the monumental impact of data-driven decisions, this Data Science & Machine Learning with Python course emerges as a beacon for those aiming to be at the forefront of this technological renaissance. Dive in, and let's chart a Data Science & Machine Learning with Python course through the riveting landscape of data science in the UK.

This Data Science & Machine Learning with Python course covers the following topics:

• Understand foundational concepts in machine learning and data science.
• Acquire proficiency in Python and essential data analysis libraries.
• Analyse, visualise and interpret datasets effectively.
• Evaluate and compare various machine learning algorithms.
• Finalise and deploy machine learning models for predictions.
• Address challenges such as imbalanced datasets and real-time predictions.

This Data Science & Machine Learning with Python course has several modules; each module is easy to understand and delivers to-the-point content. If you need any help with any module or have any questions while studying the course, your designated tutor will provide you with continuous assistance so that you can complete each lesson in the Data Science & Machine Learning with Python course successfully and swiftly.

Data Science & Machine Learning with Python Course Curriculum:

• Module 01: Dive into machine learning, understanding its foundational concepts, classifications, and real-world applications.
• Module 02: Set up the optimal system and environment to embark on your machine learning journey with Python.
• Module 03: Delve into Python's core, mastering its essential functions and intricate data structures.
• Module 04: Unlock the power of NumPy, exploring arrays, data handling, and mathematical operations.
• Module 05: Get acquainted with Matplotlib, harnessing its capabilities for insightful data visualisation.
• Module 06: Venture into the world of Pandas, gaining prowess in data analysis and manipulation techniques.
• Module 07: Decode the CSV data file format, understanding its significance in data science.
• Module 08: Master the art of loading and reading CSV files using Python, NumPy, and Pandas.
• Module 09: Get hands-on with datasets, discerning their structure, correlation, and intricate details.
• Module 10: Delve deeper into data distributions, understanding skewness and the nuances of Gaussian and normal curves.
• Module 11: Elevate your visualisation skills, interpreting data using histograms, density, and box plots.
• Module 12: Expand your visualisation repertoire, focusing on multivariate dataset analysis using scatter and correlation plots.
• Module 13: Learn the craft of data preparation, exploring techniques like re-scaling, standardising, normalising, and binarising.
• Module 14: Unlock the potential of feature selection, mastering techniques from Chi-Squared tests to Principal Component Analysis.
• Module 15: Revisit key concepts, ensuring a solid understanding of re-sampling, training, and testing mechanisms.
• Module 16: Dive into algorithm evaluation, learning diverse techniques from K-Fold cross-validation to train-test splits.
• Module 17: Evaluate algorithms precisely, understanding metrics from log loss and ROC curves to confusion matrices.
• Module 18: Get a comprehensive overview of classification algorithms, from logistic regression to support vector machines.
• Module 19: Enhance your knowledge of regression algorithms, exploring linear regression, ridge regression, and more.
• Module 20: Sharpen your skills in comparing and selecting the most suitable machine learning models for various tasks.
• Module 21: Dive into the world of pipelines, integrating data preparation, modelling, and feature selection seamlessly.
• Module 22: Improve your models' performance with ensemble methods, bagging, boosting, and advanced parameter tuning techniques.
• Module 23: Master techniques to export, save, and load your machine learning models using Pickle and Joblib.
• Module 24: Understand the steps and intricacies of finalising a machine learning model.
• Module 25-28: Apply your knowledge to finalise models for specific, real-world datasets, focusing on classification and regression challenges.
• Module 29: Implement your models, making real-time predictions across diverse datasets.

Process of Evaluation

After studying the Data Science & Machine Learning with Python course, your skills and knowledge will be tested with an MCQ exam or assignment. You have to get a score of 60% to pass the test and get your certificate.

Certificate of Achievement

After completing this Data Science & Machine Learning with Python course, you will get your CPD-accredited digital certificate for £5.99 (each). To get the hardcopy certificate for £12.99 (each), you also have to pay the shipping charge of just £3.99 (UK) and £10.99 (International).

This course is tailored for enthusiasts interested in Data Science & Machine Learning with Python. Those looking to harness the power of Python alongside its robust libraries like Pandas, NumPy, and Matplotlib will find this curriculum invaluable. Beginners eager to understand intricate concepts like algorithm evaluation, dataset visualisation, and feature selection can greatly benefit. Moreover, professionals aiming to enhance their expertise in deploying machine learning models for real-time predictions will find the modules quite enlightening. The Data Science & Machine Learning with Python course ensures that learners are well-equipped to address nuanced challenges in data science, making it apt for those seeking a comprehensive learning experience.

This course has no prerequisite. Therefore, you don’t need any educational qualification or experience to enrol in this Data Science & Machine Learning with Python course.

• Data Scientist - £35K to £70K/year.
• Machine Learning Engineer - £40K to £80K/year.
• Data Analyst - £30K to £50K/year.
• Data Engineer - £40K to £75K/year.
• Research Scientist (Machine Learning) - £45K to £85K/year.

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Certificate of Completion - Digital Certificate

Digital certificate - £5.99

Certificate of Completion - Hard copy Certificate

Hard copy certificate - £12.99