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Top 13 FREE Data Analysis Courses with Certifications

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Hello everyone! I’m Rupnath, a data analyst professional with two years of experience. I love helping future data professionals like you find your dream jobs. On my blog, I share helpful career tips, project ideas, and insights on key skills.

I will share 13 FREE data analytics courses with certifications. These courses come from trusted platforms like Coursera, Udemy, Udacity, and DataCamp. They are structured learning paths. They help you gain important skills such as Python, SQL, and Power BI.

Let’s dive in and explore each course. I’ll highlight what you’ll learn and why it’s ideal for your data analytics journey.

Introduction: Why These Courses Matter

The demand for data analysts is rising quickly. This means we need affordable, quality training. These 13 courses can help you enter the field. They will build a solid foundation in core data analysis skills. You’ll learn Python, SQL, DBMS, statistical analysis, data visualisation, and machine learning.

At the end of this article, you’ll see a clear path to earn the abilities companies demand, all for free. I chose these courses for their practical, hands-on experience. This will prepare you for real-world data challenges.

Course 1: Intro to Data Analysis

  • Platform: Udacity

  • Level: Intermediate

  • Key Skills: Data Analysis Process, NumPy, Pandas

This free course from Udacity offers a great introduction to data analysis. You’ll discover how to analyse data. This includes asking questions and turning findings into useful actions. The course highlights two key Python libraries: NumPy and Pandas. You’ll learn to work with data using these libraries. You’ll handle both one-dimensional and two-dimensional datasets. It ends with a practical project where you’ll explore a real-world dataset and use your new skills. This hands-on experience helps solidify your understanding and build your portfolio.

Course 2: SQL for Data Analysis

  • Platform: Udacity

  • Key Skills: SQL (Basic to Advanced)

SQL is the common language of databases. This Udacity course helps you build SQL skills, from beginner to advanced. It’s made for data analysts. You will explore a variety of topics, including:

  • Basic SQL Syntax

  • Joins (Inner, Outer, Left, Right)

  • Aggregation Functions (COUNT, SUM, AVG, etc.)

  • Subqueries and Temporary Tables

  • Data Cleaning Techniques using SQL

  • Window Functions

  • Advanced Join Techniques and Performance Tuning

This course shows you how to get, change, and analyse data from relational databases. This is a key skill for any aspiring data analyst. The focus on performance tuning is especially useful. It helps you write efficient SQL queries, which are essential in professional settings.

Course 3: SQL for Data Analysis: Solving Real-World Problems with Data

  • Platform: Udemy

  • Key Skills: SQL, Introduction to Data Analysis

This Udemy course offers a great chance to improve your SQL skills, focusing on practical use. It goes beyond SQL syntax and explores the “why” of data analysis. It answers questions like:

  • Why learn data analysis?

  • Why is SQL essential for data analysis?

  • What exactly is data, and why is it important?

The course focuses on practical SQL skills. First, download and set up MySQL. It’s a well-known open-source database management system. Next, you’ll learn to use SELECT queries and filter data with the WHERE clause. You will also explore logical operators like AND and OR. Additionally, the course covers various SQL functions for calculations and data manipulation. This blend of ideas and practical training makes the course a key part of your learning journey.

Course 4: Bayesian Statistics: From Concept to Data Analysis

  • Platform: Coursera

  • Key Skills: Probability, Bayes’ Theorem, Statistical Modeling

This course explores Bayesian statistics. It is a strong framework for understanding and modelling data. You’ll learn about:

  • Probability Fundamentals

  • Bayes’ Theorem and its applications

  • Statistical Concepts for Data Analysis

  • Prior and Posterior Distributions

  • Building Statistical Models for Discrete and Continuous Data

Bayesian statistics is becoming more important in data analysis. It helps you use prior knowledge and adjust your beliefs as new data comes in. This course offers a solid base in Bayesian thinking and its real-world use in data analysis.

Course 5: Exploratory Data Analysis in Python

  • Platform: DataCamp

  • Key Skills: Exploratory Data Analysis (EDA) in Python

Exploratory Data Analysis (EDA) is the crucial first step in any data analysis project. This free DataCamp course teaches you how to perform EDA using Python. You’ll learn techniques for:

  • Getting to Know Your Dataset: Understanding its structure, variables, and distributions

  • Data Cleaning: Handling missing values, outliers, and inconsistencies

  • Identifying Relationships in Data: Exploring correlations, trends, and patterns

  • Turning EDA into Action: Drawing insights and formulating hypotheses based on your findings

The course includes techniques for:

  • Replacing missing data

  • Managing categorical variables

  • Visualising relationships over time

  • Creating new features from existing data

The hands-on projects in DataCamp’s interactive environment provide helpful real-world experience.

Course 6: Statistics with R

  • Platform: Coursera (University of Leeds)

  • Key Skills: Descriptive Statistics, Data Cleaning, Data Visualization in R

This Coursera course helps you analyse statistics and visualise data using R. R is a popular programming language in data science. You’ll explore:

  • Graphical Summaries of Data: Creating histograms, box plots, scatter plots, etc.

  • Data Cleaning Techniques in R: Handling missing values and outliers

  • Creating Effective Visualizations: Communicating insights through clear and compelling visuals

This course shifts the focus from Python to the R ecosystem. You’ll expand your skills and become a more flexible data analyst.

Course 7: Data Visualization with Tableau

  • Platform: Udacity

  • Key Skills: Tableau (Data Visualization, Dashboard Design, Storytelling)

Data visualization is an essential skill for communicating data insights effectively. This course focuses on Tableau, a leading data visualization tool. You’ll learn to create:

  • Interactive Data Visualizations: Charts, graphs, and maps

  • Dashboards: Combining multiple visualizations into a cohesive story

  • Data Storytelling: Communicating insights effectively through visual narratives

Tableau is popular in the industry. This course will help you get a great start in mastering this powerful tool.

Course 8: Data Preparation and Analysis Using Python

  • Platform: Coursera

  • Key Skills:

    • Data Preparation

    • Correlation Analysis

    • Market Basket Analysis

    • Regression

    • Decision Trees

    • Model Evaluation

This course builds on your Python skills. You’ll discover advanced data analysis methods and get a look at machine learning.

  • Data Preparation: Cleaning and transforming data for analysis

  • Correlation Analysis: Measuring and visualizing relationships between variables

  • Market Basket Analysis: Identifying associations between items in transaction data

  • Segmentation Techniques: Partitioning, segmenting, and clustering data

  • Regression Analysis: Linear and Logistic Regression

  • Decision Trees: Building tree-based models for prediction

  • Model Evaluation: Assessing the performance of your models

This course connects data analysis and machine learning. You’ll get a taste of predictive modeling.

Course 9: Python for Data Analysis

  • Platform: Udemy

  • Key Skills: Python for Data Analysis, Data Processing, Data Visualization

This Udemy course provides a focused introduction to using Python for data analysis. It covers:

  • Data Processing Techniques in Python

  • Creating Data Visualizations in Python

This course is a great way to strengthen your Python skills for data analysis.

Course 10: Master Data Analysis with Python: Intro to Pandas

  • Platform: Udemy

  • Key Skills: Pandas (DataFrames, Series, Data Manipulation, Data Exploration)

This course explores the Pandas library, a key tool for data analysis in Python. You’ll learn about:

  • DataFrames and Series: The core data structures in Pandas

  • Handling Data Types and Missing Values

  • Setting Meaningful Indexes

  • The Five-Step Process for Data Exploration

  • Selecting Subsets of Data

Mastering Pandas is essential for efficiently manipulating and analyzing data in Python.

Course 11: Applied Analysis

  • Platform: Coursera

  • Key Skills: Pandas (DataFrames, Series, Selecting, Filtering)

This Coursera course focuses specifically on applying Pandas for data manipulation. You’ll learn about:

  • DataFrames and Series

  • Selecting and Filtering Data

This is a concise and focused course for mastering essential Pandas operations.

Course 12: Introduction to Machine Learning with Python

  • Platform: Udemy

  • Key Skills: Machine Learning (Regression, Classification, Clustering)

This Udemy course provides an introduction to machine learning using Python. You’ll explore different types of machine learning models, including:

  • Regression Models: Simple Linear Regression, Multiple Linear Regression

  • Classification Models: Logistic Regression, Decision Trees, Random Forests

  • Clustering Models: K-Means Clustering

This course shows you the exciting world of predictive modeling. It’s a valuable skill for data analysts who want to grow their abilities.

Course 13: Statistics for Data Analysis

  • Platform: Udacity

  • Key Skills:

    • Statistical Methods

    • Data Visualization

    • Central Tendency

    • Variable Standardization

    • Normal Distribution

    • Hypothesis Testing

This course provides a comprehensive overview of statistical methods relevant to data analysis. It covers:

  • Statistical Methods for Data Analysis

  • Visualizing Data for Statistical Insights

  • Measures of Central Tendency (Mean, Median, Mode)

  • Variable Standardization and Normalization

  • Understanding the Normal Distribution

  • Hypothesis Testing

A strong foundation in statistics is essential for drawing meaningful insights from data.

Conclusion

I’ve shared various courses that cover key data analysis skills. This covers Python programming, SQL, statistical analysis, data visualization, and a basic look at ML. Pick the courses that match your learning style and career goals. All these courses are FREE, providing great value and a risk-free way to explore data. Don’t wait—start your data analysis journey today. I’m excited to see you succeed in this rewarding field. Please share and subscribe to my blog for more valuable content. Thank you for reading, and good luck on your data journey.

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