So guys here are some of the best courses for data science, tableau, SQL, and Python on Udemy. These are some courses that even I did on my Data Science journey to enhance my skills.

The first course on this list **‘Complete Python Bootcamp From Zero to Hero in Python’ by Jose Portilla is my personal favorite**. So without any further due, let’s do it.

## 1. Complete Python Bootcamp From Zero to Hero in Python

### What you’ll learn

- Learn to use Python professionally, learning both Python 2 and Python 3!
- Create games with Python, like Tic Tac Toe and Blackjack!
- Learn advanced Python features, like the collections module and how to work with timestamps!
- Learn to use Object Oriented Programming with classes!

- Understand complex topics, like decorators.
- Understand how to use both the Jupyter Notebook and create .py files
- Get an understanding of how to create GUIs in the Jupyter Notebook system!
- Build a complete understanding of Python from the ground up!

### Requirements

- Access to a computer with an internet connection.

## 2. Statistics for Data Science and Business Analysis

### What you’ll learn

- Understand the fundamentals of statistics
- Learn how to work with different types of data
- How to plot different types of data
- Calculate the measures of central tendency, asymmetry, and variability
- Calculate correlation and covariance
- Distinguish and work with different types of distributions
- Estimate confidence intervals

- Perform hypothesis testing
- Make data driven decisions
- Understand the mechanics of regression analysis
- Carry out regression analysis
- Use and understand dummy variables
- Understand the concepts needed for data science even with Python and R!

### Requirements

- Absolutely no experience is required. We will start from the basics and gradually build up your knowledge. Everything is in the course.
- A willingness to learn and practice

## 3. R Programming A-Z™: R For Data Science With Real Exercises!

### What you’ll learn

- Learn to program in R at a good level
- Learn how to use R Studio
- Learn the core principles of programming
- Learn how to create vectors in R
- Learn how to create variables
- Learn about integer, double, logical, character and other types in R
- Learn how to create a while() loop and a for() loop in R
- Learn how to build and use matrices in R

- Learn the matrix() function, learn rbind() and cbind()
- Learn how to install packages in R
- Learn how to customize R studio to suit your preferences
- Understand the Law of Large Numbers
- Understand the Normal distribution
- Practice working with statistical data in R
- Practice working with financial data in R
- Practice working with sports data in R

### Requirements

- No prior knowledge or experience is needed. Only a passion to be successful!

## 4. SQL – MySQL for Data Analytics and Business Intelligence

### What you’ll learn

- Become an expert in SQL
- Learn how to code in SQL
- Boost your resume by learning an in-demand skill
- Create, design, and operate with SQL databases
- Start using MySQL – the #1 Database Management System
- Prepare for SQL developer, Database administrator, Business Analyst, and Business Intelligence job opportunities
- Adopt professionally tested SQL best practices
- Gain theoretical insights about relational databases
- Work with a sophisticated real-life database throughout the course
- Get maximum preparation for real-life database management
- Add data analytical tools to your skillset
- Develop business intuition while solving tasks with big data
- Study relational database management theory that you will need in your workplace every day
- Learn how to create a database from scratch

- The ability to take control of your dataset – insert, update, and delete records from your database
- Be confident while working with constraints and relating data tables
- Become a proficient MySQL Workbench user
- Understand complex topics, like decorators.
- Acquire top-notch coding techniques and best practices
- Know how to answer specific business questions by using SQL’s aggregate functions
- Handle complex SQL joins with ease
- Approach more advanced topics in programming like SQL’s triggers, sequences, local and global variables, indexes, and more
- Merge coding skills and business acumen to solve complex analytical problems
- Become a proficient SQL user by writing flawless and efficient queries
- Tons of exercises that will solidify your knowledge
- The freedom to query anything you like from a database

### Requirements

- No prior experience is required. We will start from the very basics

## 5. Tableau A-Z: Hands-On Tableau Training for Data Science

### What you’ll learn

- Install Tableau Desktop 2020
- Connect Tableau to various Datasets: Excel and CSV files
- Create Barcharts
- Create Area Charts
- Create Maps
- Create Scatterplots
- Create Piecharts
- Create Treemaps
- Create Interactive Dashboards
- Create Storylines
- Understand Types of Joins and how they work
- Work with Data Blending in Tableau
- Create Table Calculations
- UnWork with Parameters
- Create Dual Axis Charts

- Create Calculated Fields
- Create Calculated Fields in a Blend
- Export Results from Tableau into Powerpoint, Word, and other software
- Work with Timeseries Data (two methods)
- Creating Data Extracts in Tableau
- Understand Aggregation, Granularity, and Level of Detail
- Adding Filters and Quick Filters
- Create Data Hierarchies
- Adding Actions to Dashboards (filters & highlighting)
- Assigning Geographical Roles to Data Elements
- Advanced Data Preparation (including latest updates in Tableau)

### Requirements

- Basic knowledge of computers.

## 6. Machine Learning A-Z™: Hands-On Python & R In Data Science

### What you’ll learn

- Master Machine Learning on Python & R
- Have a great intuition of many Machine Learning models
- Make accurate predictions
- Make powerful analysis
- Make robust Machine Learning models
- Create strong added value to your business
- Use Machine Learning for personal purpose
- Handle specific topics like Reinforcement Learning, NLP and Deep Learning

- Handle advanced techniques like Dimensionality Reduction
- Know which Machine Learning model to choose for each type of problem
- Build an army of powerful Machine Learning models and know how to combine them to solve any problem

### Requirements

- Just some high school mathematics level.

## 7. Python for Data Science and Machine Learning Bootcamp

### What you’ll learn

- Use Python for Data Science and Machine Learning
- Use Spark for Big Data Analysis
- Implement Machine Learning Algorithms
- Learn to use NumPy for Numerical Data
- Learn to use Pandas for Data Analysis
- Learn to use Matplotlib for Python Plotting
- Learn to use Seaborn for statistical plots
- Use Plotly for interactive dynamic visualizations

- Use SciKit-Learn for Machine Learning Tasks
- K-Means Clustering
- Logistic Regression
- Linear Regression
- Random Forest and Decision Trees
- Natural Language Processing and Spam Filters
- Neural Networks
- Support Vector Machines

### Requirements

- Some programming experience
- Admin permissions to download files

## 8. The Data Science Course: Complete Data Science Bootcamp

### What you’ll learn

- The course provides the entire toolbox you need to become a data scientist
- Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
- Impress interviewers by showing an understanding of the data science field
- Learn how to pre-process data
- Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
- Start coding in Python and learn how to use it for statistical analysis
- Perform linear and logistic regressions in Python
- Carry out cluster and factor analysis

- Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
- Apply your skills to real-life business cases
- Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
- Unfold the power of deep neural networks
- Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
- Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations

### Requirements

- No prior experience is required. We will start from the very basics
- You’ll need to install Anaconda. We will show you how to do that step by step
- Microsoft Excel 2003, 2010, 2013, 2016, or 365

## 9. Machine Learning, Data Science and Deep Learning with Python

### What you’ll learn

- Build artificial neural networks with Tensorflow and Keras
- Classify images, data, and sentiments using deep learning
- Make predictions using linear regression, polynomial regression, and multivariate regression
- Data Visualization with MatPlotLib and Seaborn
- Implement machine learning at massive scale with Apache Spark’s MLLib
- Understand reinforcement learning – and how to build a Pac-Man bot

- Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA
- Use train/test and K-Fold cross validation to choose and tune your models
- Build a movie recommender system using item-based and user-based collaborative filtering
- Clean your input data to remove outliers
- Design and evaluate A/B tests using T-Tests and P-Values

### Requirements

- You’ll need a desktop computer (Windows, Mac, or Linux) capable of running Anaconda 3 or newer. The course will walk you through installing the necessary free software.
- Some prior coding or scripting experience is required.
- At least high school-level math skills will be required.

## 10. Data Science: Natural Language Processing (NLP) in Python

### What you’ll learn

- Write your own cipher decryption algorithm using genetic algorithms and language modeling with Markov models
- Write your own spam detection code in Python
- Write your own sentiment analysis code in Python

- Perform latent semantic analysis or latent semantic indexing in Python
- Have an idea of how to write your own article spinner in Python

### Requirements

- Install Python, it’s free!
- You should be at least somewhat comfortable writing Python code
- Know how to install numerical libraries for Python such as Numpy, Scipy, Scikit-learn, Matplotlib, and BeautifulSoup
- Take my free Numpy prerequisites course (it’s FREE, no excuses!) to learn about Numpy, Matplotlib, Pandas, and Scikit-Learn, as well as Machine Learning basics
- Optional: If you want to understand the math parts, linear algebra and probability are helpful

**Check out my Machine Learning, Deep Learning, OpenCV, NLP, and Flask projects.**