Data Analytics, Data Science, & Machine Learning - All in 1 — 92% OFF Coupon

From Theory to Hands-on Projects - EVERYTHING to Master Data Analytics, Data Science and Machine Learning in 1 Course.

★4.5 out of 5
10,142 students
Created by Analytics AI
English
Updated May 2026

Quick Facts — Course Summary

Here's a comprehensive overview of Data Analytics, Data Science, & Machine Learning - All in 1 — including pricing, duration, instructor credentials, curriculum highlights, and coupon validity. All data is verified against Udemy listings on May 30, 2026.

Here's a quick overview of everything you need to know about Data Analytics, Data Science, & Machine Learning - All in 1 before you enroll:

•Course Name: Data Analytics, Data Science, & Machine Learning - All in 1
•Platform: Udemy
•Instructor: Analytics AI
•Coupon Last Verified: May 30, 2026
•Level: Advanced
•Topic: Business
•Subtopic: Data Science
•Total Time: 66h of video content
•Language: English
•Access Type: Unlimited lifetime access + updates
•Certificate: Included upon completion from Udemy
•Main Skills: Understand data science foundations, applications, and the path to becoming a data scientist. · Analyze data using Python programming with variables, loops, functions, and OOP. · Apply statistics and probability with distributions, hypothesis testing, and inference in Python.
•Requirements: Access to computer and internet · Basic computer literacy
•Current Price: $12.99 (was $169.99). You save $157.00 with 92% discount.
•How to Apply: Click the coupon button to activate your discount automatically
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Skills You'll Master

By completing Data Analytics, Data Science, & Machine Learning - All in 1, you'll gain practical, job-ready skills in Business. The curriculum is designed by Analytics AI to ensure you develop real-world competencies that employers value.

By the end of Data Analytics, Data Science, & Machine Learning - All in 1, you'll have these practical skills:

✓Understand data science foundations, applications, and the path to becoming a data scientist. .
✓Analyze data using Python programming with variables, loops, functions, and OOP. .
✓Apply statistics and probability with distributions, hypothesis testing, and inference in Python. .
✓Perform data cleaning, transformation, and EDA using pandas and NumPy. .
✓Visualize data with Python using bar charts, histograms, scatterplots, heatmaps, and box plots. .
✓Build regression, classification, and clustering models with scikit-learn and evaluate performance. .
✓Master advanced ML techniques like cross-validation, feature engineering, regularization, and hyperparameter tuning. .
✓Implement ensemble learning methods such as Random Forest, AdaBoost, CatBoost, LightGBM, and XGBoost. .
✓Explore deep learning with neural networks and TensorFlow, from preprocessing to model evaluation. .
✓Gain hands-on experience through real-life projects and assessments to build a strong portfolio. .
✓Acquire Excel, SQL, Python, Power BI, and ChatGPT skills to prepare for a data analyst career. .
✓Learn data analysis foundations with statistics, hypothesis testing, and machine learning. .
✓Use Excel for data cleaning, manipulation, formulas, functions, graphs, and charts. .
✓Apply Excel advanced tools like pivot tables, Analysis ToolPak, and interactive dashboards. .
✓Understand RDBMS fundamentals including keys, data types, and relational models. .
✓Work with MySQL for table manipulation, constraints, indices, filtering, and joins. .
✓Learn Python basics including variables, data types, lists, dictionaries, loops, and functions. .
✓Master Python for data cleaning, manipulation, preprocessing, and transformation. .
✓Use Python for visualization, exploratory analysis, statistics, and ML modeling. .
✓Utilize ChatGPT for data manipulation, merging, pivot tables, and conditional logic. .
✓Apply ChatGPT for predictive analytics with Random Forest and ML models. .
✓Learn Power BI for data manipulation, analysis, and dashboard insights. .
✓Create professional, story-driven dashboards in Power BI with impactful visuals. .
✓Complete 30+ assignments, 120+ coding exercises, and 10 quizzes with 100+ questions. .
✓Accomplish 4 capstone projects: bank churn analysis, sports analytics, HR data management and website performance analysis. .
✓Accomplish 7 AI projects: Image Captioning, Chatbot, Voice Assistant, Text to Image, Video Summarizer, Language Translator and Data Analyst AI.

What You Need Before Starting

Before enrolling in Data Analytics, Data Science, & Machine Learning - All in 1, review the recommended prerequisites below. Meeting these requirements will help you follow the course material effectively and get the most out of your learning experience on Udemy.

Before enrolling in Data Analytics, Data Science, & Machine Learning - All in 1, make sure you have:

•Access to computer and internet
•Basic computer literacy
•No coding experience required
•Dedication, patience and perseverance

About This Udemy Course

The following is the full official course description for Data Analytics, Data Science, & Machine Learning - All in 1 as published on Udemy by instructor Analytics AI:

Embark on a transformative journey into the world of Data Analytics, Data Science, and Machine Learning, where you’ll learn the essential skills, tools, and mindsets to become a successful data professional. This comprehensive program is designed to take you from beginner to advanced, equipping you with the knowledge and practical experience needed to excel in the field.

Whether you’re looking to kickstart a career in data analytics or enhance your existing skills, this course will empower you to succeed in the dynamic world of data. Join us on this exciting path and unlock your potential in just 60–100 days of disciplined learning.

Why This Course Matters

Most learners struggle with fragmented resources, inconsistent guidance, or theory-heavy content that doesn’t build real competence. This course solves that problem. It’s structured to provide step-by-step, cumulative, and daily progress — helping you turn knowledge into capability, and capability into career readiness.

We are in the AI revolution, and every industry is transforming with tools like ChatGPT, Stable Diffusion, and AI copilots for writing, coding, design, analytics, and more. This course ensures you don’t just learn theory — you’ll build real-world solutions that make you job-ready.

1. Foundations of Data Analytics, Data Science & Python
  • Learn how to think like a data scientist, not just how to write code.
  • Python fundamentals: variables, loops, conditionals, functions, data structures.
  • Clean, modular, reusable coding practices for data workflows.
  • Importing and handling real-world datasets with Pandas and NumPy.
  • Data types, memory optimization, and performance tuning.
  • A-Z data cleaning and manipulation techniques: sorting, filtering, pivot tables, and charts.
2. Excel, SQL, Python & Power BI Proficiency
  • Excel: Manipulate data, perform calculations, and create visualizations.
  • SQL: Query and manipulate relational databases, perform joins, aggregations, and optimize queries.
  • Python: Analyze and visualize data with Pandas, NumPy, and Matplotlib. Automate workflows and create advanced dashboards.
  • ChatGPT for Data Analysis: Handle missing data, outliers, dataset merging, pivoting, and even advanced ML predictions.
  • Power BI: Connect to multiple data sources, clean and transform data, and design interactive dashboards and reports.
3. Exploratory Data Analysis (EDA)
  • Understand the shape, distributions, and essence of raw data.
  • Advanced grouping, filtering, and reshaping with Pandas.
  • Visualize relationships using Matplotlib and Seaborn (histograms, pairplots, heatmaps).
  • Develop strong data intuition and hypothesis-forming skills.
4. Probability, Statistics & Mathematics for Data Science
  • Probability distributions: Normal, Binomial, Poisson, Exponential, Uniform.
  • Descriptive statistics: mean, median, mode, variance, standard deviation.
  • Inferential statistics: confidence intervals, hypothesis testing, chi-square, t-tests, ANOVA.
  • Linear Algebra: vectors, matrices, dot products, PCA foundations.
  • Calculus: derivatives, gradients, optimization, and gradient descent for ML.
5. Machine Learning & Feature Engineering
  • Complete ML workflow: preprocessing, training, validating, testing.
  • Algorithms: Logistic Regression, Decision Trees, Random Forests, KNN, Ensemble Methods.
  • Handling class imbalance (SMOTE, stratified sampling).
  • Model evaluation: accuracy, precision, recall, F1-score, ROC-AUC.
  • Bias-variance tradeoff, underfitting vs. overfitting.
  • Feature engineering: encoding categorical variables, scaling/normalizing, building pipelines.
  • Hyperparameter tuning (GridSearchCV, RandomizedSearchCV).
6. Deep Learning & Generative AI
  • Neural networks with TensorFlow: tensors, activation functions, backpropagation, optimizers.
  • Build and train models step by step, fine-tune, and evaluate with accuracy/loss metrics.
  • Prompt Engineering: Chain-of-Thought, Tree-of-Thought, structured prompts.
  • Generative AI Tools & Use Cases: text, image, code, audio, and video generation.
  • Real-world AI applications: chatbots, translators, voice assistants, text-to-image, video summarization.
7. Projects & Hands-On Practice
  • Over 30+ assignments, 120+ coding exercises, and 10 quizzes.
  • Capstone Projects:
  • Bank Data Analysis
  • Sports Data Analysis
  • Fraud Detection & Classification
  • Striker Ranking (End-to-End ML Deployment)
  • Generative AI Projects (7 full-scale builds):
  • Image Captioning AI
  • Chatbot with LLaMA2/Gemma
  • AI Voice Assistant
  • Text-to-Image Generator
  • AI Video Summarizer
  • Language Translator
  • AI Data Analyst
Benefits of the Course
  • Career Readiness: Gain the technical and professional skills to qualify for data analyst and data scientist roles.
  • Versatility: Become proficient in Excel, SQL, Python, Power BI, TensorFlow, Hugging Face, and more.
  • Problem-Solving Skills: Sharpen your analytical and critical thinking abilities.
  • Portfolio Enhancement: Build a robust portfolio of real-world projects to showcase in interviews.
  • Industry-Relevant Learning: Stay up-to-date with modern data and AI methodologies.
How This Course Will Transform You

By following this structured roadmap, you’ll be able to:
  • Confidently work with real datasets and perform independent analysis.
  • Build, tune, and deploy machine learning and AI models.
  • Understand the mathematical foundations of modern data science.
  • Create a project portfolio strong enough for job interviews or freelance opportunities.
  • Qualify for entry-to-intermediate level roles in Data Science, ML Engineering, or Analytics.
  • One Honest Limitation
This course is not for learners who prefer highly animated, passive learning. The teaching style is text-based, code-first, and explanation-rich — emphasizing depth, clarity, and practical application. Diagrams and visuals are included, but the focus is on doing, thinking, and building.

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Is the Data Analytics, Data Science, & Machine Learning - All in 1 Coupon Worth It?

Expert review by Andrew Derek, Lead Course Analyst at CoursesWyn.•Last updated: May 30, 2026.

Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, Data Analytics, Data Science, & Machine Learning - All in 1 is a high-value resource for learners seeking to build skills inBusiness. Taught by Analytics AI on Udemy, the 66h course provides a structured progression from foundational concepts to advanced techniques— making it suitable for learners at all levels. The current coupon reduces the price by 92%, from $169.99 to $12.99, removing the primary financial barrier to enrollment.

✓What We Like (Pros)

  • Verified 92% price reduction makes this course accessible to learners on any budget.
  • Aggregate student rating of 4.5 out of 5 indicates high learner satisfaction.
  • Strong enrollment base with over 10,142 students demonstrates course popularity and trust.
  • Includes an official Udemy completion certificate and lifetime access to all future content updates.

!Keep in Mind (Cons)

The following limitations should be considered before enrolling in Data Analytics, Data Science, & Machine Learning - All in 1:

  • The depth of Business coverage may be challenging for absolute beginners without the listed prerequisites.
  • Lifetime access is contingent on the continued operation of the Udemy platform.
  • Hands-on projects and quizzes require additional time investment beyond video watch time.
Final Verdict: Worth It
This course offers exceptional value with current pricing
✓

Course Rating Summary

Data Analytics, Data Science, & Machine Learning - All in 1 has earned an aggregate rating of 4.5 out of 5 from 10,142 verified student reviews on Udemy. Below is the detailed rating distribution showing learner satisfaction across all star levels.

4.5
★★★★★
10,142 Verified Ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

* Rating distribution is approximated from the aggregate score. Sourced from Udemy.

Instructor Profile

Analytics AI is the instructor behind Data Analytics, Data Science, & Machine Learning - All in 1 on Udemy. Learn about their teaching background, subject matter expertise, and instructional approach to determine if this course matches your learning style.

Data Analytics, Data Science, & Machine Learning - All in 1 is taught by Analytics AI, a Udemy instructor specializing in Business. For the full instructor biography, professional credentials, and a complete list of their courses, visit the official instructor profile on Udemy.

•Instructor Name: Analytics AI
•Subject Area: Business
•Teaching Approach: Practical, project-based instruction focused on real-world application of Business skills.

Frequently Asked Questions

The following questions and answers cover the most common queries about Data Analytics, Data Science, & Machine Learning - All in 1, its coupon code, pricing, and enrollment process.

About the Author

AD

Andrew Derek

Lead Course Analyst at CoursesWyn with 8+ years of experience evaluating online learning platforms. I've analyzed 500+ Udemy courses and helped thousands of learners choose the right courses for their career goals.

⭐4.8/5 Rating
✓Trusted by 10K+ Students

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