Data Analytics Roadmap - Hero Section
2026 Edition • AI-Powered Learning

DATA ANALYTICS
WITH AI ROADMAP

A comprehensive 6-month learning journey from fundamentals to advanced predictive analytics. Master data analytics with AI integration, perfect for Marketing, Sales, and Risk Analytics careers.

6 Tháng Học Tập
70% Hands-On Projects
15-20 Giờ / Tuần
AI+ Integration Focus
Roadmap Overview

Your Journey to Data Mastery

Designed for beginners transitioning into Data Analytics with strong AI integration, predictive modeling, and modern generative AI tools

Duration
6 Months
Time Commitment
15-20h/week
Learning Style
70% Practice
AI Integration
Full Stack

Four Learning Pillars

1

Data Analytics Knowledge

Master statistics, business metrics, and analytical frameworks that form the foundation of data-driven decision making

2

Data Tools & Technologies

Excel, SQL, Python, Power BI, Tableau - become proficient in the essential toolkit of modern data analysts

3

AI & Machine Learning

Predictive analytics, ML algorithms, AutoML, and Generative AI integration for cutting-edge insights

4

Soft Skills & Business Acumen

Communication, storytelling, stakeholder management - translate data insights into business impact

6-Month Journey

Your Learning Roadmap

A structured path from fundamentals to advanced analytics, designed to build skills progressively with hands-on projects at every step

Phase 1

FUNDAMENTAL

Months 1-2 • Building Strong Foundations

Month 1: Business Statistics & Excel For Analysis

4 weeks

Week 1-2: Data Analytics foundations, business statistics, Excel fundamentals

Week 3-4: Advanced Excel (Pivot tables, VLOOKUP, INDEX-MATCH), data visualization basics, Power Pivot, Interactive dashboard

1
2

Month 2: SQL For Data Analysis

4 weeks

Week 5-6: SQL fundamentals (SELECT, JOINs, aggregations), database concepts, CTEs

Week 7-8: Advanced SQL: Window functions, Views, Database manipulation

Phase 2

INTERMEDIATE

Months 3-4 • Deepening Technical Skills

Month 3: Analytical Thinking & BI Tools (Power BI)

4 weeks

Week 9-10: Build automatic dashboard with Power/Tableu, Data modeling, DAX

Week 11-12: Apply Analytical Thinking into Data Analysis cases

3
4

Month 4: Python Analytics Foundation

4 weeks

Week 13-14: Advanced Pandas & NumPy, data cleaning, customer churn analysis project

Week 15-16: Data visualization (Matplotlib/Seaborn), EDA

Phase 3

ADVANCED

Months 5-6 • Mastering Predictive Analytics & AI

Month 5: Machine Learning Mastery With AI

4 weeks

Week 17-18: Basic ML algorithms for business analytics cases

Week 19-20: Advanced ML algorithms (classification, regression, clustering), model evaluation, customer LTV prediction

5
6

Month 6: Industry Apps & Portfolio

4 weeks

Week 21-22: Domain-specific applications (Marketing/Sales/Risk Analytics), end-to-end capstone project

Week 23-24: Advanced AI tools, LLM integration, portfolio building, resume optimization, final capstone

Essential Tools 2026

Generative AI Assistants

Leverage cutting-edge AI assistants to accelerate your data analytics workflow

From code generation to complex data analysis

ChatGPT

OpenAI

The most popular AI assistant for data analytics. Advanced Data Analysis mode enables CSV processing, statistical analysis, and instant visualizations with natural language commands.

Code generation (SQL, Python, R)

Data cleaning & preprocessing

Statistical analysis & visualization

Best For

Quick data exploration, writing SQL queries, debugging code

Watch Tutorial

Claude

Anthropic

Advanced AI with exceptional reasoning capabilities and 200K context window. Artifacts feature creates interactive dashboards and comprehensive analytical reports in real-time.

Long-form data analysis (200K context)

Complex reasoning & insights

Interactive dashboards with Artifacts

Best For

Analyzing large datasets, generating comprehensive reports, complex reasoning

Watch Tutorial

Gemini

Google

Google's multimodal AI with deep integration into Google Workspace. Seamlessly works with Google Sheets, BigQuery, and Looker for end-to-end analytics workflows.

Google Workspace integration

BigQuery SQL assistance

Multimodal data analysis (text, images, code)

Best For

Google ecosystem users, BigQuery queries, collaborative analytics

Watch Tutorial

GitHub Copilot

GitHub

AI pair programmer that lives in your IDE. Intelligent code suggestions and completions specifically trained on data analysis patterns and best practices.

Real-time code completion

Context-aware suggestions

IDE integration (VS Code, Jupyter)

Best For

Writing data analysis scripts, Python/R development, code efficiency

Watch Tutorial
MONTH 1

Business Statistics & Excel Mastery

Build a solid foundation in data analytics, master Excel techniques, and understand core statistical concepts

Week 1-2

Data Analytics Foundations & Statistics

  • What is Data Analytics? Types: Descriptive, Diagnostic, Predictive, Prescriptive
  • Data types: Quantitative vs Qualitative, Structured vs Unstructured
  • Basic statistics: Mean, median, mode, variance, standard deviation,
  • Inferential statistics: Sampling, Hypothesis testing, Probability
Week 3-4

Advanced Excel & Data Visualization Basics

  • Pivot tables, VLOOKUP, XLOOKUP, INDEX-MATCH
  • Conditional formatting and data validation
  • Charts and dashboards in Excel, Power Pivot, Power Query
  • Data visualization principles (choosing the right chart)
Mini Project: Sales Performance Dashboard in Excel
MONTH 2

SQL For Data Analysis + First AI Tools

Master database querying with SQL, and leverage AI tools for accelerated learning

Week 5-6

SQL Fundamentals

  • Database concepts: Tables, rows, columns, keys
  • SELECT, WHERE, GROUP BY, ORDER BY
  • JOINs (INNER, LEFT, RIGHT, FULL)
  • Aggregations: COUNT, SUM, AVG, MAX, MIN
  • Subqueries and CTEs (Common Table Expressions)
  • Practice: SQLZoo, LeetCode SQL problems
Week 7-8

Advanced SQL For Database management & Query

  • Performance Optimization & Query Tuning
  • Database Design & Management (for Analysts)
  • Data Transformation & ETL with SQL
  • SQL for BI & Dashboarding
  • First AI experience: Using ChatGPT/Claude for code assistance
Mini Project: Advanced Analytics Use Cases with SQL

Soft Skills Development

Essential professional skills for Month 1-2

Critical thinking and problem-solving frameworks
Business communication basics
How to ask good questions
Understanding stakeholder needs
MONTH 3

Analytical Thinking & BI Tools (Power BI)

Master advanced Analytical Thinking techniques, data modeling, and create powerful interactive dashboards with Power BI

Week 9-10

Advanced Analytical Thinking & Problem Solving Strategy

  • Problem Framing & Business Context Mastery
  • Hypothesis-Driven Thinking (Thinking Before Data)
  • Structured Problem Decomposition (MECE & Beyond)
  • Analytical Strategy Design
  • Storytelling & Persuasive Problem Solving
Project: Data Analysis Report for Business Problem
Week 11-12

Data Analysis & Build Automatic Dashboard With BI Tools

  • Power BI: Data connections, Power Query, DAX basics
  • Creating interactive dashboards and reports
  • Tableau: Connecting to data, building visualizations
  • Dashboard design best practices
  • Publishing and sharing reports
Project: Marketing Campaign Performance Dashboard
MONTH 4

Python for Data Analysis

Master Python data manipulation with Pandas, create stunning visualizations.

Week 13-14

Advanced Python - Pandas & NumPy

  • Pandas: DataFrames, Series, indexing, filtering
  • Data cleaning: handling missing values, duplicates, outliers
  • GroupBy operations and aggregations
  • Merging and joining datasets
  • NumPy arrays and vectorization
Project: Data cleaning & EDA with Pandas
Week 15-16

Data Visualization with Python

  • Matplotlib and Seaborn for data visualization
  • Exploratory Data Analysis (EDA) techniques
  • Introduction to Machine Learning concepts
  • Supervised vs Unsupervised learning
  • Simple Linear Regression with scikit-learn
Project: Sales Forecasting with Linear Regression

Soft Skills Development

Essential professional skills for Month 3-4

Data storytelling and narrative building
Presentation skills for technical audiences
Translating insights into business recommendations
Building a data analytics portfolio
MONTH 5

Predictive Analytics & Machine Learning Mastery

Master advanced machine learning algorithms, build predictive models, and leverage cutting-edge AutoML tools

Week 17-18

Advanced Machine Learning Algorithms

  • Classification: Logistic Regression, Decision Trees, Random Forest
  • Regression: Multiple regression, Polynomial regression
  • Clustering: K-Means, Hierarchical clustering
  • Model evaluation: Accuracy, Precision, Recall, F1-Score, ROC-AUC
  • Cross-validation and hyperparameter tuning
Project: Customer Lifetime Value Prediction
Week 19-20

AutoML & Modern AI Tools

  • Introduction to AutoML: H2O.ai, PyCaret, AutoGluon
  • Feature engineering automation
  • Model selection and ensemble methods
  • Deploying ML models (basics)
  • Generative AI for Analytics: Using ChatGPT/Claude for code generation, debugging, insights
Project: Automated Predictive Model Pipeline with AutoML
MONTH 6 - FINAL

Industry Applications & Portfolio Projects

Apply your skills to real-world domains, build an impressive portfolio, and prepare for your data analytics career

Week 21-22

Domain-Specific Applications

Marketing Analytics:

  • Customer segmentation (RFM analysis, clustering)
  • Marketing mix modeling (MMM)
  • A/B testing and campaign optimization
  • Attribution modeling

Sales Analytics:

  • Sales forecasting (time series with Prophet, ARIMA)
  • Lead scoring with ML
  • Pipeline analysis and conversion optimization
  • Sales territory optimization

Risk Analytics:

  • Credit risk modeling
  • Fraud detection with anomaly detection
  • Churn prediction and prevention
  • Risk scoring models
Major Project (Choose 1): End-to-end analytics project in your chosen domain
Week 23-24

Advanced AI & Portfolio Building

  • Generative AI deep dive: Prompting strategies for data analysis
  • LLM integration: Using GPT-4, Claude API for insights
  • AI-powered dashboards and reporting
  • Natural Language Processing (NLP) basics for text analytics
  • Building your data portfolio: GitHub, portfolio website
  • Creating case studies from your projects
  • Resume and LinkedIn optimization for data roles
Final Capstone: AI-Enhanced Analytics Solution

Soft Skills Development

Essential professional skills for Month 5-6

Executive presentations and C-level communication
Stakeholder management and influencing without authority
Project management for analytics projects
Ethical considerations in data and AI
Networking and personal branding
Project Portfolio

Build Your Project Portfolio

Hands-on project ideas across Marketing, Sales, and Risk Analytics to showcase your skills

Marketing Analytics
Sales Analytics
Risk Analytics
Beginner

Email Campaign Performance Dashboard

Build an interactive dashboard analyzing email campaign metrics: open rates, click-through rates, conversions, and ROI.

Excel Power BI Visualization
Intermediate

Customer Segmentation - RFM Analysis

Segment customers based on Recency, Frequency, and Monetary value using clustering algorithms for targeted marketing.

Python SQL K-Means
Advanced

Marketing Attribution Model

Build a multi-touch attribution model to understand which marketing channels contribute most to conversions using ML.

Python ML AutoML
Beginner

Sales Performance Dashboard

Create a comprehensive sales dashboard tracking KPIs: revenue, conversion rates, top products, and sales team performance.

Excel Tableau SQL
Intermediate

Sales Forecasting Model

Build time series forecasting models to predict future sales using historical data and seasonal patterns.

Python Time Series Prophet
Advanced

Customer Lifetime Value Prediction

Predict customer lifetime value using ML to identify high-value customers and optimize acquisition strategies.

Python ML Regression
Beginner

Credit Risk Dashboard

Develop a dashboard to monitor credit risk metrics: default rates, credit scores distribution, and risk exposure.

Excel Power BI SQL
Intermediate

Fraud Detection System

Build an anomaly detection system to identify fraudulent transactions using statistical methods and pattern recognition.

Python SQL Anomaly Detection
Advanced

Credit Scoring Model with ML

Develop an ML-based credit scoring model to assess borrower creditworthiness and predict default probability.

Python ML Classification
Start Your Journey Today

Ready to Become a Data Analyst?

Join thousands of learners who are transforming their careers with AI-powered data analytics. Your journey to becoming a data professional starts now!

2000+
Học Viên
20+
Doanh Nghiệp Đối Tác
90%
Tỷ Lệ Hài Lòng
4.8/5
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