About this programme
Programme overview
The Data Science by Chelsea AIcademy is a comprehensive, self-paced program designed to take you from foundational statistics and Python to advanced machine learning and generative AI. Designed to be completed in 28 weeks part-time or about 14 weeks full-time, the curriculum requires a commitment of 12 to 15 hours per week. You will master core data science skills, including data wrangling with SQL and pandas, statistical experimentation, and data visualization using tools like Power BI and Tableau.|
Beyond the basics, this program dives deep into modern artificial intelligence and real-world application. You will get hands-on experience with deep learning, NLP, and generative AI, learning how to build prompt engineering tools, fine-tune models, and deploy RAG-based applications. The learning experience is entirely project-driven; rather than just absorbing theory, you will prove your skills by completing rigorous deliverables at the end of every phase, such as end-to-end machine learning pipelines and deployed model endpoints.
Finally, the course is built around your ultimate goal: landing a job offer. The final phases of the syllabus are explicitly dedicated to career readiness, where you will build a live professional portfolio showcasing two to three polished capstone projects. You will also receive dedicated guidance on crafting an ATS-optimized data science resume and completing thorough interview preparation, which includes tackling over 50 technical questions and participating in recorded mock interviews to ensure you are ready for the job market.
Curriculum
What you'll learn
Linear Algebra Essentials
Lesson 1: Linear Algebra EssentialsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 0 — Orientation & Math FoundationsWeek: 1Category: CoreLesson Descrip...
Probability Basics
Lesson 2: Probability BasicsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 0 — Orientation & Math FoundationsWeek: 1Category: CoreLesson DescriptionThi...
Python Setup
Lesson 3: Python SetupLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 0 — Orientation & Math FoundationsWeek: 1Category: CoreLesson DescriptionThis less...
The Data Science Lifecycle
Lesson 4: The Data Science LifecycleLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 0 — Orientation & Math FoundationsWeek: 1Category: CoreLesson Descri...
Descriptive Statistics
Lesson 5: Descriptive StatisticsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 0 — Orientation & Math FoundationsWeek: 1Category: CoreLesson Descriptio...
Math & Statistics Foundations with Learning Tracker
pandas & NumPy
Lesson 1: pandas & NumPyLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 1 — Python for Data ScienceWeek: 2–3Category: CoreLesson DescriptionThis lesson...
Functions & OOP Basics
Lesson 2: Functions & OOP BasicsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 1 — Python for Data ScienceWeek: 2–3Category: CoreLesson DescriptionThis...
Comprehensions
Lesson 3: ComprehensionsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 1 — Python for Data ScienceWeek: 2–3Category: CoreLesson DescriptionThis lesson intr...
APIs & File I/O
Lesson 4: APIs & File I/OLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 1 — Python for Data ScienceWeek: 2–3Category: CoreLesson DescriptionThis lesson...
Virtual Environments
Lesson 5: Virtual EnvironmentsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 1 — Python for Data ScienceWeek: 2–3Category: CoreLesson DescriptionThis lesso...
Multi-File Data Cleaning & Validation Using Pandas
Joins & Aggregations
Lesson 1: Joins & AggregationsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 2 — SQL & Data WranglingWeek: 4–5Category: CoreLesson DescriptionThis...
Window Functions
Lesson 2: Window FunctionsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 2 — SQL & Data WranglingWeek: 4–5Category: CoreLesson DescriptionThis lesson i...
Common Table Expressions (CTEs)
Lesson 3: Common Table Expressions (CTEs)Learning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 2 — SQL & Data WranglingWeek: 4–5Category: CoreLesson Descripti...
Real Relational Schemas
Lesson 4: Real Relational SchemasLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 2 — SQL & Data WranglingWeek: 4–5Category: CoreLesson DescriptionThis l...
Intro to NoSQL (MongoDB)
Lesson 5: Intro to NoSQL (MongoDB)Learning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 2 — SQL & Data WranglingWeek: 4–5Category: CoreLesson DescriptionThis...
SQL Analytics on a Multi-Table Database
Probability Distributions
Lesson 1: Probability DistributionsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 3 — Statistics & ExperimentationWeek: 6–7Category: CoreLesson Descrip...
Hypothesis Testing
Lesson 2: Hypothesis TestingLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 3 — Statistics & ExperimentationWeek: 6–7Category: CoreLesson DescriptionThi...
Confidence Intervals
Lesson 3: Confidence IntervalsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 3 — Statistics & ExperimentationWeek: 6–7Category: CoreLesson DescriptionT...
A/B Test Design
Lesson 4: A/B Test DesignLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 3 — Statistics & ExperimentationWeek: 6–7Category: CoreLesson DescriptionThis l...
Intro to Bayesian Thinking
Lesson 5: Intro to Bayesian ThinkingLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 3 — Statistics & ExperimentationWeek: 6–7Category: CoreLesson Descri...
Experiment Design, Statistical Significance Testing & Product Recommendation
Matplotlib & Seaborn
Lesson 1: Matplotlib & SeabornLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 4 — Data Visualization & StorytellingWeek: 8–9Category: CoreLesson Des...
Power BI or Tableau
Lesson 2: Power BI or TableauLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 4 — Data Visualization & StorytellingWeek: 8–9Category: CoreLesson Descript...
Choosing the Right Chart
Lesson 3: Choosing the Right ChartLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 4 — Data Visualization & StorytellingWeek: 8–9Category: CoreLesson Des...
Dashboard Design
Lesson 4: Dashboard DesignLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 4 — Data Visualization & StorytellingWeek: 8–9Category: CoreLesson Description...
Narrative Structure
Lesson 5: Narrative StructureLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 4 — Data Visualization & StorytellingWeek: 8–9Category: CoreLesson Descript...
Interactive Dashboard & Insight Memo
Regression & Classification
Lesson 1: Regression & ClassificationLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 5 — Machine Learning FundamentalsWeek: 10–12Category: CoreLesson De...
Trees & Ensembles
Lesson 2: Trees & EnsemblesLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 5 — Machine Learning FundamentalsWeek: 10–12Category: CoreLesson DescriptionT...
Cross-Validation
Lesson 3: Cross-ValidationLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 5 — Machine Learning FundamentalsWeek: 10–12Category: CoreLesson DescriptionThis l...
Feature Engineering
Lesson 4: Feature EngineeringLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 5 — Machine Learning FundamentalsWeek: 10–12Category: CoreLesson DescriptionThi...
scikit-learn Pipelines
Lesson 5: scikit-learn PipelinesLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 5 — Machine Learning FundamentalsWeek: 10–12Category: CoreLesson Description...
End-to-End Supervised Learning Pipeline
Neural Network Fundamentals
Lesson 1: Neural Network FundamentalsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 6 — Deep Learning & NLPWeek: 13–15Category: AILesson DescriptionThi...
CNNs for Images
Lesson 2: CNNs for ImagesLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 6 — Deep Learning & NLPWeek: 13–15Category: AILesson DescriptionThis lesson int...
RNNs & Transformers
Lesson 3: RNNs & TransformersLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 6 — Deep Learning & NLPWeek: 13–15Category: AILesson DescriptionThis le...
Tokenization & Embeddings
Lesson 4: Tokenization & EmbeddingsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 6 — Deep Learning & NLPWeek: 13–15Category: AILesson DescriptionT...
Hugging Face Basics
Lesson 5: Hugging Face BasicsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 6 — Deep Learning & NLPWeek: 13–15Category: AILesson DescriptionThis lesson...
Fine-Tuned Text or Image Classification Model
Prompt Engineering
Lesson 1: Prompt EngineeringLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 7 — Generative AI & LLMsWeek: 16–17Category: AILesson DescriptionThis lesson...
Retrieval-Augmented Generation
Lesson 2: Retrieval-Augmented GenerationLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 7 — Generative AI & LLMsWeek: 16–17Category: AILesson Descriptio...
Claude / OpenAI APIs
Lesson 3: Claude / OpenAI APIsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 7 — Generative AI & LLMsWeek: 16–17Category: AILesson DescriptionThis less...
Lightweight Fine-Tuning
Lesson 4: Lightweight Fine-TuningLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 7 — Generative AI & LLMsWeek: 16–17Category: AILesson DescriptionThis l...
AI Agents & Tool Use
Lesson 5: AI Agents & Tool UseLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 7 — Generative AI & LLMsWeek: 16–17Category: AILesson DescriptionThis...
Untitled
FastAPI / Flask Model APIs
Lesson 1: FastAPI / Flask Model APIsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 8 — MLOps & DeploymentWeek: 18–19Category: AILesson DescriptionThis...
Docker
Lesson 2: DockerLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 8 — MLOps & DeploymentWeek: 18–19Category: AILesson DescriptionThis lesson introduces Do...
CI/CD Basics
Lesson 3: CI/CD BasicsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 8 — MLOps & DeploymentWeek: 18–19Category: AILesson DescriptionThis lesson introdu...
Model Monitoring & Drift
Lesson 4: Model Monitoring & DriftLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 8 — MLOps & DeploymentWeek: 18–19Category: AILesson DescriptionThi...
Cloud Deployment (AWS/GCP)
Lesson 5: Cloud Deployment (AWS/GCP)Learning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 8 — MLOps & DeploymentWeek: 18–19Category: AILesson DescriptionThis...
Model Deployment & Monitoring
End-to-End Problem Framing
Lesson 1: End-to-End Problem FramingLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 9 — Capstone ProjectsWeek: 20–21Category: CareerLesson DescriptionThis l...
Combining ML + Deployment + Visualization
Lesson 2: Combining ML + Deployment + VisualizationLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 9 — Capstone ProjectsWeek: 20–21Category: CareerLesson De...
Documentation & Reproducibility
Lesson 3: Documentation & ReproducibilityLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 9 — Capstone ProjectsWeek: 20–21Category: CareerLesson Descript...
Final Capstone Portfolio Project
Site Structure
Lesson 1: Site StructureLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 10 — Portfolio CreationWeek: 22Category: CareerLesson DescriptionThis lesson introdu...
Case-Study Format
Lesson 2: Case-Study FormatLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 10 — Portfolio CreationWeek: 22Category: CareerLesson DescriptionThis lesson intr...
GitHub Hygiene
Lesson 3: GitHub HygieneLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 10 — Portfolio CreationWeek: 22Category: CareerLesson DescriptionThis lesson focuses...
Untitled
ATS Formatting
Lesson 1: ATS FormattingLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 11 — Resume BuildingWeek: 23Category: CareerLesson DescriptionThis lesson introduces...
Quantified Bullets
Lesson 2: Quantified BulletsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 11 — Resume BuildingWeek: 23Category: CareerLesson DescriptionThis lesson focuse...
LinkedIn Optimization
Lesson 3: LinkedIn OptimizationLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 11 — Resume BuildingWeek: 23Category: CareerLesson DescriptionThis lesson foc...
ATS-Optimized Data Science Resume
ML & Stats Theory
Lesson 1: ML & Stats TheoryLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 12 — Interview PreparationWeek: 24–25Category: CareerLesson DescriptionThis l...
SQL & Python Coding
Lesson 2: SQL & Python CodingLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 12 — Interview PreparationWeek: 24–25Category: CareerLesson DescriptionThis...
Case & Product-Sense
Lesson 3: Case & Product-SenseLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 12 — Interview PreparationWeek: 24–25Category: CareerLesson DescriptionThi...
Behavioral / STAR
Lesson 4: Behavioral / STARLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 12 — Interview PreparationWeek: 24–25Category: CareerLesson DescriptionThis lesso...
Mock Interviews
Lesson 5: Mock InterviewsLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 12 — Interview PreparationWeek: 24–25Category: CareerLesson DescriptionThis lesson...
Interview Preparation & Mock Interviews
Target Company List
Lesson 1: Target Company ListLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 13 — Job Search & OutreachWeek: 26–28Category: CareerLesson DescriptionThis...
Referrals & Cold Outreach
Lesson 2: Referrals & Cold OutreachLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 13 — Job Search & OutreachWeek: 26–28Category: CareerLesson Descr...
Application Tracking
Lesson 3: Application TrackingLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 13 — Job Search & OutreachWeek: 26–28Category: CareerLesson DescriptionThi...
Offer Negotiation
Lesson 4: Offer NegotiationLearning Format: Self-Paced CurriculumRecommended Learning Time: 12–15 Hours per WeekPhase: 13 — Job Search & OutreachWeek: 26–28Category: CareerLesson DescriptionThis l...
Job Search Execution & Application Tracking
Free Counselling — 30 Minutes
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