Packt
Data Science Essentials: Analysis, Statistics, and ML Specialization
Packt

Data Science Essentials: Analysis, Statistics, and ML Specialization

Master Statistics, SQL, and Python Dashboards. Perform analysis, visualize data, build dashboards, and create ML models using SQL and Python.

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Get in-depth knowledge of a subject
Intermediate level

Recommended experience

2 months to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

2 months to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Analyze data using statistical tools, probability, and hypothesis testing.

  • Query and manipulate databases using foundational and advanced SQL techniques.

  • Visualize and explore datasets using Python libraries like NumPy, Pandas, and Matplotlib.

  • Build interactive dashboards and implement ML models with Plotly Dash and Python.

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Taught in English
Recently updated!

September 2025

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Specialization - 5 course series

What you'll learn

  • Master key descriptive statistics concepts, including mean, median, and skewness.

  • Gain a solid understanding of probability theory, including Bayes' Theorem and the Law of Large Numbers.

  • Learn hypothesis testing techniques such as t-tests and understand Type I and Type II errors.

  • Apply regression analysis techniques, including linear and logistic regression, to solve data problems.

Skills you'll gain

Category: Statistical Methods
Category: Probability Distribution
Category: Statistical Inference
Category: Statistics
Category: Regression Analysis
Category: Statistical Modeling
Category: Probability
Category: Statistical Analysis
Category: Analytics
Category: Data Science
Category: Applied Machine Learning
Category: Data Analysis
Category: Correlation Analysis
Category: Data-Driven Decision-Making
Category: Predictive Analytics
Category: Probability & Statistics
Master SQL for Data Analysis

Master SQL for Data Analysis

Course 210 hours

What you'll learn

  • Master key SQL commands and queries for data retrieval, manipulation, and analysis

  • Understand the relational model, including tables, keys, and indexes

  • Perform advanced data analysis using subqueries, conditional logic, and window functions

  • Simplify complex queries with views and common table expressions (CTEs)

Skills you'll gain

Category: Performance Tuning

What you'll learn

  • Understand the core concepts of NumPy arrays, including their benefits over Python lists.

  • Gain proficiency in visualizing data using various types of plots in Matplotlib.

  • Learn how to manipulate and analyze data with Pandas for data science tasks.

  • Explore the basics of machine learning models such as classification and regression.

Skills you'll gain

Category: Machine Learning
Category: Regression Analysis
Category: Classification And Regression Tree (CART)
Category: Probability Distribution
Category: Data Manipulation
Category: Data Visualization Software
Category: NumPy
Category: Pandas (Python Package)
Category: Linear Algebra
Category: Scatter Plots
Category: Jupyter
Category: Data Science
Category: Data Import/Export

What you'll learn

  • Identify the core components and structure of a Plotly Dash dashboard.

  • Explain the role of callbacks in making dashboards interactive.

  • Break down complex dashboard layouts into manageable sections using HTML and CSS.

  • Assess the effectiveness of dashboard interactivity through real-time data updates.

Skills you'll gain

Category: Interactive Data Visualization
Category: Jupyter
Category: Plotly
Category: Dashboard
Category: Real Time Data
Category: Data Visualization Software
Category: HTML and CSS
Category: Python Programming
Category: UI Components
Category: Pandas (Python Package)
Category: Data Analysis

What you'll learn

  • Gain a strong foundation in machine learning terminology, algorithms, and real-world applications.

  • Master key statistical concepts like probability, hypothesis testing, and data distributions for ML tasks.

  • Develop proficiency in Python, including core libraries like NumPy and Pandas for data analysis.

Skills you'll gain

Category: Pandas (Python Package)
Category: NumPy
Category: Python Programming
Category: Machine Learning
Category: Statistical Analysis
Category: Applied Machine Learning
Category: Data Manipulation
Category: Probability & Statistics
Category: Statistical Hypothesis Testing
Category: Data Science
Category: Probability Distribution

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Instructor

Packt - Course Instructors
Packt
964 Courses205,430 learners

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