Skip to content
  1. Online
  2. IT
  3. Artificial Intelligence
Data Science & Artificial Intelligence Bootcamp cover image
Play overlay
Preview this course

Data Science & Artificial Intelligence Bootcamp
Xcel Learning

Learn Without Limits — Free Start, Free Certificate, Lifetime Access

Summary

Price
£15 inc VAT
Study method
Online, On Demand 
Course format
12 PDFs and 1 Assessment
Duration
1.3 hours · Self-paced
Qualification
No formal qualification
Certificates
  • Reed Courses Certificate of Completion - Free
Assessment details
  • Review Questions and Assessments (included in price)
Additional info
  • Tutor is available to students

Add to basket or enquire

Overview

Data Science & Artificial Intelligence Bootcamp Data Science and Artificial Intelligence Bootcamp is a comprehensive, industry-aligned program designed to equip learners with the knowledge and practical skills required to thrive in the modern data driven world. This bootcamp takes participants on a structured journey from foundational concepts such as data science workflows, Python programming, and essential mathematics to advanced topics including machine learning, deep learning, and real-world AI applications. Through hands-on projects, practical case studies, and an end-to-end capstone experience, learners gain the ability to collect, analyze, and transform data into meaningful insights and intelligent solutions. The program also emphasizes model deployment, MLOps practices, and career readiness, ensuring graduates are prepared for professional roles in data science and AI. Whether transitioning careers or advancing technical expertise, this bootcamp empowers learners to build impactful, ethical, and scalable AI solutions with confidence.

Certificates

Assessment details

Review Questions and Assessments

Included in course price

Curriculum

This course contains

Format: 12 PDFs and 1 Assessment

Duration: 1h and 20m

Description

Discover the Exciting Topics Awaited in this Enriching Course!

Chapter 1: Foundations of Data Science

  1. Introduction to Data Science Ecosystem
  2. Types of Data and Data Sources
  3. Data Science Workflow & Lifecycle
  4. Tools & Environments (Python, Jupyter, Git)
  5. Ethical Considerations in Data Science

Chapter 2: Python Programming for Data Science

  1. Python Basics Refresher (Syntax, Variables, Data Types)
  2. Control Flow & Functions
  3. Working with Libraries (NumPy, Pandas)
  4. File Handling & Data I/O
  5. Writing Clean & Modular Code

Chapter 3: Mathematics for AI & Data Science

  1. Linear Algebra Essentials
  2. Probability Fundamentals
  3. Statistics Basics
  4. Optimization Concepts
  5. Mathematical Intuition for ML

Chapter 4: Data Wrangling & Preprocessing

  1. Data Cleaning Techniques
  2. Handling Missing Values
  3. Feature Engineering Basics
  4. Data Transformation & Scaling
  5. Working with Large Datasets

Chapter 5: Exploratory Data Analysis (EDA)

  1. Descriptive Statistics
  2. Data Visualization Principles
  3. Visualization with Matplotlib & Seaborn
  4. Identifying Patterns & Trends
  5. Storytelling with Data

Chapter 6: Machine Learning Fundamentals

  1. Introduction to Machine Learning Types
  2. 1 Supervised vs Unsupervised Learning
  3. Training, Validation, and Testing
  4. Bias-Variance Tradeoff
  5. Model Evaluation Metrics

Chapter 7: Supervised Learning Algorithms

  1. Linear Regression & Regularization
  2. Logistic Regression
  3. Decision Trees & Random Forests
  4. Support Vector Machines
  5. K-Nearest Neighbors

Chapter 8: Unsupervised Learning Techniques

  1. Clustering Algorithms (K-Means, DBSCAN)
  2. Dimensionality Reduction (PCA, t-SNE)
  3. Anomaly Detection
  4. Market Basket Analysis
  5. Use Cases of Unsupervised Learning

Chapter 9: Deep Learning Foundations

  1. Neural Network Basics
  2. Activation Functions & Loss Functions
  3. Backpropagation Explained
  4. Frameworks (TensorFlow, PyTorch)
  5. Training Deep Models Effectively

Chapter 10: Advanced AI Applications

  1. Computer Vision Basics
  2. Natural Language Processing (NLP)
  3. Recommendation Systems
  4. Time Series Forecasting
  5. Generative AI Overview

Chapter 11: Model Deployment & MLOps

  1. Model Serialization & Packaging
  2. Building APIs for ML Models
  3. Cloud Deployment Basics
  4. Monitoring & Maintenance
  5. CI/CD for Machine Learning

Chapter 12: Capstone & Career Preparation

  1. End-to-End Capstone Project
  2. Building a Data Science Portfolio
  3. Resume & LinkedIn Optimization
  4. Interview Preparation & Case Studies
  5. Career Paths in AI & Data Science

Don't miss out on the chance to discover your full potential. Enroll today and open the door to a world of opportunities. Receive an exclusive digital certificate upon completing the course!

Who is this course for?

This course is designed for aspiring data scientists, software developers, analysts, and professionals looking to transition into artificial intelligence. It suits beginners with basic programming knowledge as well as experienced individuals aiming to upskill in machine learning, data analysis, and AI tools to solve real-world problems and advance their careers.

Questions and answers

There are currently no Q&As for this course. Be the first to ask a question.

Ask a question

Reviews

Currently there are no reviews for this course. Be the first to leave a review.

Leave a review

Legal information

This course is advertised on Reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

A regulated qualification is delivered by a learning institution which is regulated by a government body. In England, the government body which regulates courses is Ofqual. Ofqual regulated qualifications sit on the Regulated Qualifications Framework (RQF), which can help students understand how different qualifications in different fields compare to each other. The framework also helps students to understand what qualifications they need to progress towards a higher learning goal, such as a university degree or equivalent higher education award.

An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.
View all
Similar subjects: Artificial Intelligence, IT
Related searches: Data science courses, Online courses

Zopa Bank Limited trading as DivideBuy is authorised by the Prudential Regulation Authority and regulated by the Financial Conduct Authority and the Prudential Regulation Authority, and entered on the Financial Services Register (800542). Zopa Bank Limited (10627575) is incorporated in England & Wales and has its registered office at: Zopa Bank, Level 12, 20 Water Street, Canary Wharf, London E14 5GX. VAT Number 281765280.