Best Data Science Courses to Learn in March 2025
Looking to enhance your skills? We’ve curated a list of the top-rated data science courses available this month. These courses are highly rated by students and offer comprehensive learning experiences.
10. Python Data Science: Data Prep & EDA with Python
Instructor: Maven Analytics
Learn Python + Pandas for data cleaning, profiling & EDA, and prep data for machine learning & data science with Python
Course Highlights:
- Rating: 4.79 ⭐ (1133 reviews)
- Students Enrolled: 7082
- Course Length: 31031 hours
- Number of Lectures: 180
- Number of Quizzes: 7
Python Data Science: Data Prep & EDA with Python, has an average rating of 4.79, with 180 lectures, 7 quizzes, based on 1133 reviews, and has 7082 subscribers.
You will learn about Master the core building blocks of Python for data science BEFORE applying machine learning algorithms Scope data science projects by clearly defining the goals, techniques, and data sources needed for your analysis Import and export flat files, Excel workbooks, and SQL database tables using Pandas Clean data by converting data types, handling common data issues, and creating new columns for analysis Perform exploratory data analysis (EDA) by sorting, filtering, grouping, and visualizing data to discover patterns and insights Prepare data for machine learning models by joining tables, aggregating rows, and applying feature engineering techniques This course is ideal for individuals who are Data scientists looking to learn core techniques and best practices for data prep and exploratory data analysis or Python users who want to build the core skills required before applying AI and machine learning models or Data analysts or BI experts looking to transition into a data science role or Anyone interested in learning one of the most popular open source programming languages in the world It is particularly useful for Data scientists looking to learn core techniques and best practices for data prep and exploratory data analysis or Python users who want to build the core skills required before applying AI and machine learning models or Data analysts or BI experts looking to transition into a data science role or Anyone interested in learning one of the most popular open source programming languages in the world.
Learn More About Python Data Science: Data Prep & EDA with Python
What You Will Learn
- Master the core building blocks of Python for data science BEFORE applying machine learning algorithms
- Scope data science projects by clearly defining the goals, techniques, and data sources needed for your analysis
- Import and export flat files, Excel workbooks, and SQL database tables using Pandas
- Clean data by converting data types, handling common data issues, and creating new columns for analysis
- Perform exploratory data analysis (EDA) by sorting, filtering, grouping, and visualizing data to discover patterns and insights
- Prepare data for machine learning models by joining tables, aggregating rows, and applying feature engineering techniques
9. Python for Machine Learning & Data Science Masterclass
Instructor: Jose Portilla
Learn about Data Science and Machine Learning with Python! Including Numpy, Pandas, Matplotlib, Scikit-Learn and more!
Course Highlights:
- Rating: 4.62 ⭐ (16992 reviews)
- Students Enrolled: 118980
- Course Length: 158496 hours
- Number of Lectures: 232
- Number of Quizzes: 4
Python for Machine Learning & Data Science Masterclass, has an average rating of 4.62, with 232 lectures, 4 quizzes, based on 16992 reviews, and has 118980 subscribers.
You will learn about You will learn how to use data science and machine learning with Python. You will create data pipeline workflows to analyze, visualize, and gain insights from data. You will build a portfolio of data science projects with real world data. You will be able to analyze your own data sets and gain insights through data science. Master critical data science skills. Understand Machine Learning from top to bottom. Replicate real-world situations and data reports. Learn NumPy for numerical processing with Python. Conduct feature engineering on real world case studies. Learn Pandas for data manipulation with Python. Create supervised machine learning algorithms to predict classes. Learn Matplotlib to create fully customized data visualizations with Python. Create regression machine learning algorithms for predicting continuous values. Learn Seaborn to create beautiful statistical plots with Python. Construct a modern portfolio of data science and machine learning resume projects. Learn how to use Scikit-learn to apply powerful machine learning algorithms. Get set-up quickly with the Anaconda data science stack environment. Learn best practices for real-world data sets. Understand the full product workflow for the machine learning lifecycle. Explore how to deploy your machine learning models as interactive APIs. This course is ideal for individuals who are Beginner Python developers curious about Machine Learning and Data Science with Python It is particularly useful for Beginner Python developers curious about Machine Learning and Data Science with Python.
Learn More About Python for Machine Learning & Data Science Masterclass
What You Will Learn
- You will learn how to use data science and machine learning with Python.
- You will create data pipeline workflows to analyze, visualize, and gain insights from data.
- You will build a portfolio of data science projects with real world data.
- You will be able to analyze your own data sets and gain insights through data science.
- Master critical data science skills.
- Understand Machine Learning from top to bottom.
- Replicate real-world situations and data reports.
- Learn NumPy for numerical processing with Python.
- Conduct feature engineering on real world case studies.
- Learn Pandas for data manipulation with Python.
- Create supervised machine learning algorithms to predict classes.
- Learn Matplotlib to create fully customized data visualizations with Python.
- Create regression machine learning algorithms for predicting continuous values.
- Learn Seaborn to create beautiful statistical plots with Python.
- Construct a modern portfolio of data science and machine learning resume projects.
- Learn how to use Scikit-learn to apply powerful machine learning algorithms.
- Get set-up quickly with the Anaconda data science stack environment.
- Learn best practices for real-world data sets.
- Understand the full product workflow for the machine learning lifecycle.
- Explore how to deploy your machine learning models as interactive APIs.
8. Mathematics-Basics to Advanced for Data Science And GenAI
Instructor: Krish Naik
Build Strong math foundation with linear algebra,stats,probability,differential calculus for mastering data science
Course Highlights:
- Rating: 4.56 ⭐ (1573 reviews)
- Students Enrolled: 14934
- Course Length: 82548 hours
- Number of Lectures: 97
- Number of Quizzes: 0
Mathematics-Basics to Advanced for Data Science And GenAI, has an average rating of 4.56, with 97 lectures, based on 1573 reviews, and has 14934 subscribers.
You will learn about Master Calculus: Understand derivatives and integrals, and apply them in optimizing machine learning algorithms and data analysis tasks. Learn Linear Algebra: Grasp vectors, matrices, and eigenvalues, essential for building and understanding advanced data science models. Understand Probability: Dive into probability theory, crucial for making informed predictions and working with uncertainty in data. Apply Statistics: Gain practical skills in statistical analysis, helping you make data-driven decisions and interpret results effectively. This course is ideal for individuals who are Aspiring Data Scientists: Individuals looking to build a strong mathematical foundation essential for mastering data science and machine learning. or Data Science Beginners: Those who are new to data science and want to understand the core mathematical concepts that drive data science algorithms. or Professionals Transitioning into Data Science: Engineers, analysts, or professionals from other fields seeking to acquire the mathematical skills necessary for a career shift into data science. or Students and Academics: Students pursuing studies in data science, computer science, or related fields who need a comprehensive understanding of mathematics for data science applications. or Lifelong Learners: Anyone with a passion for learning and a desire to understand how mathematics powers the world of data science, even without prior experience in the field. or This course is tailored to equip learners with the essential mathematical tools needed to excel in data science, regardless of their current level of expertise. It is particularly useful for Aspiring Data Scientists: Individuals looking to build a strong mathematical foundation essential for mastering data science and machine learning. or Data Science Beginners: Those who are new to data science and want to understand the core mathematical concepts that drive data science algorithms. or Professionals Transitioning into Data Science: Engineers, analysts, or professionals from other fields seeking to acquire the mathematical skills necessary for a career shift into data science. or Students and Academics: Students pursuing studies in data science, computer science, or related fields who need a comprehensive understanding of mathematics for data science applications. or Lifelong Learners: Anyone with a passion for learning and a desire to understand how mathematics powers the world of data science, even without prior experience in the field. or This course is tailored to equip learners with the essential mathematical tools needed to excel in data science, regardless of their current level of expertise.
Learn More About Mathematics-Basics to Advanced for Data Science And GenAI
What You Will Learn
- Master Calculus: Understand derivatives and integrals, and apply them in optimizing machine learning algorithms and data analysis tasks.
- Learn Linear Algebra: Grasp vectors, matrices, and eigenvalues, essential for building and understanding advanced data science models.
- Understand Probability: Dive into probability theory, crucial for making informed predictions and working with uncertainty in data.
- Apply Statistics: Gain practical skills in statistical analysis, helping you make data-driven decisions and interpret results effectively.
7. From Zero to Pro Data Science & AI Advanced Full Course 2025
Instructor: Vivian Aranha
Master Data Science, AI, and Machine Learning with hands-on projects in Python, Deep Learning, Big Data, and Analytics
Course Highlights:
- Rating: 4.64 ⭐ (150 reviews)
- Students Enrolled: 10646
- Course Length: 174958 hours
- Number of Lectures: 243
- Number of Quizzes: 1
From Zero to Pro Data Science & AI Advanced Full Course 2025, has an average rating of 4.64, with 243 lectures, 1 quizzes, based on 150 reviews, and has 10646 subscribers.
You will learn about Understand Data Science Workflow: Master the end-to-end data science lifecycle, from data collection to model deployment. Data Collection Techniques: Learn to gather data from APIs, databases, and web scraping. Data Preprocessing: Clean and preprocess raw data for analysis and modeling. Exploratory Data Analysis (EDA): Uncover patterns and trends in datasets using visualization tools. Feature Engineering: Create and optimize features to improve model performance. Machine Learning Models: Build regression, classification, and clustering models using scikit-learn. Deep Learning Techniques: Train neural networks with TensorFlow and PyTorch. Model Deployment: Serve AI models using Flask, FastAPI, and Docker. Big Data Handling: Work with large datasets using tools like Hadoop and Spark. Ethical AI Practices: Understand data privacy, bias mitigation, and AI governance. This course is ideal for individuals who are Aspiring Data Scientists: Individuals who want to start a career in data science but don’t know where to begin. or Students and Graduates: Learners from diverse educational backgrounds looking to add data science to their skill set. or Professionals Seeking a Career Switch: Working professionals aiming to transition into data-centric roles like Data Analyst, Machine Learning Engineer, or AI Specialist. or Tech Enthusiasts: Curious minds eager to understand how data can drive decisions and power intelligent systems. or Business Professionals: Decision-makers and managers looking to leverage data insights to improve strategy and operations. or Freelancers and Entrepreneurs: Individuals aiming to build data-driven solutions or AI-powered products. It is particularly useful for Aspiring Data Scientists: Individuals who want to start a career in data science but don’t know where to begin. or Students and Graduates: Learners from diverse educational backgrounds looking to add data science to their skill set. or Professionals Seeking a Career Switch: Working professionals aiming to transition into data-centric roles like Data Analyst, Machine Learning Engineer, or AI Specialist. or Tech Enthusiasts: Curious minds eager to understand how data can drive decisions and power intelligent systems. or Business Professionals: Decision-makers and managers looking to leverage data insights to improve strategy and operations. or Freelancers and Entrepreneurs: Individuals aiming to build data-driven solutions or AI-powered products.
Learn More About From Zero to Pro Data Science & AI Advanced Full Course 2025
What You Will Learn
- Understand Data Science Workflow: Master the end-to-end data science lifecycle, from data collection to model deployment.
- Data Collection Techniques: Learn to gather data from APIs, databases, and web scraping.
- Data Preprocessing: Clean and preprocess raw data for analysis and modeling.
- Exploratory Data Analysis (EDA): Uncover patterns and trends in datasets using visualization tools.
- Feature Engineering: Create and optimize features to improve model performance.
- Machine Learning Models: Build regression, classification, and clustering models using scikit-learn.
- Deep Learning Techniques: Train neural networks with TensorFlow and PyTorch.
- Model Deployment: Serve AI models using Flask, FastAPI, and Docker.
- Big Data Handling: Work with large datasets using tools like Hadoop and Spark.
- Ethical AI Practices: Understand data privacy, bias mitigation, and AI governance.
6. Python for Data Science and Machine Learning Bootcamp
Instructor: Jose Portilla
Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!
Course Highlights:
- Rating: 4.59 ⭐ (149389 reviews)
- Students Enrolled: 755562
- Course Length: 89200 hours
- Number of Lectures: 184
- Number of Quizzes: 1
Python for Data Science and Machine Learning Bootcamp, has an average rating of 4.59, with 184 lectures, 1 quizzes, based on 149389 reviews, and has 755562 subscribers.
You will learn about 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 This course is ideal for individuals who are This course is meant for people with at least some programming experience It is particularly useful for This course is meant for people with at least some programming experience.
Learn More About Python for Data Science and Machine Learning Bootcamp
What You Will 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
5. Data Science Methods and Algorithms [2025]
Instructor: Henrik Johansson
Learn Data Science Methods and Algorithms with Pandas and Python [2025]
Course Highlights:
- Rating: 4.91 ⭐ (204 reviews)
- Students Enrolled: 1217
- Course Length: 165194 hours
- Number of Lectures: 86
- Number of Quizzes: 0
![Data Science Methods and Algorithms [2025]](https://img-c.udemycdn.com/course/480x270/6019702_cfc8.jpg)
Data Science Methods and Algorithms [2025], has an average rating of 4.91, with 86 lectures, based on 204 reviews, and has 1217 subscribers.
You will learn about Knowledge about Data Science methods, algorithms, theory, best practices, and tasks Deep hands-on knowledge of Data Science and know how to handle common Data Science tasks with confidence Detailed and deep Master knowledge of Regression, Prediction, Classification, Supervised Learning, Cluster Analysis, and Unsupervised Learning Hands-on knowledge of Scikit-learn, Statsmodels, Matplotlib, Seaborn, and some other Python libraries Advanced knowledge of A.I. prediction models and automatic model creation Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources Option: To use the Anaconda Distribution (for Windows, Mac, Linux) Master the Python 3 programming language for Data Handling Master Pandas 2 and 3 for Advanced Data Handling This course is ideal for individuals who are This course is for you, regardless if you are a beginner or an experienced Data Scientist or This course is for you, regardless if you have a Ph.D. or no education or experience at all It is particularly useful for This course is for you, regardless if you are a beginner or an experienced Data Scientist or This course is for you, regardless if you have a Ph.D. or no education or experience at all.
Learn More About Data Science Methods and Algorithms [2025]
What You Will Learn
- Knowledge about Data Science methods, algorithms, theory, best practices, and tasks
- Deep hands-on knowledge of Data Science and know how to handle common Data Science tasks with confidence
- Detailed and deep Master knowledge of Regression, Prediction, Classification, Supervised Learning, Cluster Analysis, and Unsupervised Learning
- Hands-on knowledge of Scikit-learn, Statsmodels, Matplotlib, Seaborn, and some other Python libraries
- Advanced knowledge of A.I. prediction models and automatic model creation
- Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources
- Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
- Master the Python 3 programming language for Data Handling
- Master Pandas 2 and 3 for Advanced Data Handling
4. Complete A.I. & Machine Learning, Data Science Bootcamp
Instructor: Andrei Neagoie
Learn Data Science, Data Analysis, Machine Learning (Artificial Intelligence) and Python with Tensorflow, Pandas & more!
Course Highlights:
- Rating: 4.6 ⭐ (25837 reviews)
- Students Enrolled: 140208
- Course Length: 156166 hours
- Number of Lectures: 384
- Number of Quizzes: 2
Complete A.I. & Machine Learning, Data Science Bootcamp, has an average rating of 4.6, with 384 lectures, 2 quizzes, based on 25837 reviews, and has 140208 subscribers.
You will learn about Become a Data Scientist and get hired Master Machine Learning and use it on the job Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0 Use modern tools that big tech companies like Google, Apple, Amazon and Meta use Present Data Science projects to management and stakeholders Learn which Machine Learning model to choose for each type of problem Real life case studies and projects to understand how things are done in the real world Learn best practices when it comes to Data Science Workflow Implement Machine Learning algorithms Learn how to program in Python using the latest Python 3 How to improve your Machine Learning Models Learn to pre process data, clean data, and analyze large data. Build a portfolio of work to have on your resume Developer Environment setup for Data Science and Machine Learning Supervised and Unsupervised Learning Machine Learning on Time Series data Explore large datasets using data visualization tools like Matplotlib and Seaborn Explore large datasets and wrangle data using Pandas Learn NumPy and how it is used in Machine Learning A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided Learn to use the popular library Scikit-learn in your projects Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry Learn to perform Classification and Regression modelling Learn how to apply Transfer Learning This course is ideal for individuals who are Anyone with zero experience (or beginner/junior) who wants to learn Machine Learning, Data Science and Python or You are a programmer that wants to extend their skills into Data Science and Machine Learning to make yourself more valuable or Anyone who wants to learn these topics from industry experts that don’t only teach, but have actually worked in the field or You’re looking for one single course to teach you about Machine learning and Data Science and get you caught up to speed with the industry or You want to learn the fundamentals and be able to truly understand the topics instead of just watching somebody code on your screen for hours without really “getting it” or You want to learn to use Deep learning and Neural Networks with your projects or You want to add value to your own business or company you work for, by using powerful Machine Learning tools. It is particularly useful for Anyone with zero experience (or beginner/junior) who wants to learn Machine Learning, Data Science and Python or You are a programmer that wants to extend their skills into Data Science and Machine Learning to make yourself more valuable or Anyone who wants to learn these topics from industry experts that don’t only teach, but have actually worked in the field or You’re looking for one single course to teach you about Machine learning and Data Science and get you caught up to speed with the industry or You want to learn the fundamentals and be able to truly understand the topics instead of just watching somebody code on your screen for hours without really “getting it” or You want to learn to use Deep learning and Neural Networks with your projects or You want to add value to your own business or company you work for, by using powerful Machine Learning tools.
Learn More About Complete A.I. & Machine Learning, Data Science Bootcamp
What You Will Learn
- Become a Data Scientist and get hired
- Master Machine Learning and use it on the job
- Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0
- Use modern tools that big tech companies like Google, Apple, Amazon and Meta use
- Present Data Science projects to management and stakeholders
- Learn which Machine Learning model to choose for each type of problem
- Real life case studies and projects to understand how things are done in the real world
- Learn best practices when it comes to Data Science Workflow
- Implement Machine Learning algorithms
- Learn how to program in Python using the latest Python 3
- How to improve your Machine Learning Models
- Learn to pre process data, clean data, and analyze large data.
- Build a portfolio of work to have on your resume
- Developer Environment setup for Data Science and Machine Learning
- Supervised and Unsupervised Learning
- Machine Learning on Time Series data
- Explore large datasets using data visualization tools like Matplotlib and Seaborn
- Explore large datasets and wrangle data using Pandas
- Learn NumPy and how it is used in Machine Learning
- A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided
- Learn to use the popular library Scikit-learn in your projects
- Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry
- Learn to perform Classification and Regression modelling
- Learn how to apply Transfer Learning
3. 100 Days of Code: The Complete Python Pro Bootcamp
Instructor: Dr. Angela Yu, Developer and Lead Instructor
Master Python by building 100 projects in 100 days. Learn data science, automation, build websites, games and apps!
Course Highlights:
- Rating: 4.7 ⭐ (354969 reviews)
- Students Enrolled: 1519440
- Course Length: 187171 hours
- Number of Lectures: 653
- Number of Quizzes: 43
100 Days of Code: The Complete Python Pro Bootcamp, has an average rating of 4.7, with 653 lectures, 43 quizzes, based on 354969 reviews, and has 1519440 subscribers.
You will learn about You will master the Python programming language by building 100 unique projects over 100 days. You will learn automation, game, app and web development, data science and machine learning all using Python. You will be able to program in Python professionally You will learn Selenium, Beautiful Soup, Request, Flask, Pandas, NumPy, Scikit Learn, Plotly, and Matplotlib. Create a portfolio of 100 Python projects to apply for developer jobs Be able to build fully fledged websites and web apps with Python Be able to use Python for data science and machine learning Build games like Blackjack, Pong and Snake using Python Build GUIs and Desktop applications with Python This course is ideal for individuals who are If you want to learn to code from scratch through building fun and useful projects, then take this course. or If you want to start your own startup by building your own websites and web apps. or If you are a complete beginner then this course will be everything you need to become a Python professional or If you are a seasoned programmer wanting to switch to Python then this is the quickest way. Learn through coding projects. or If you are an intermediate Python programmer then you know 100 days of code challenges will help you level up. It is particularly useful for If you want to learn to code from scratch through building fun and useful projects, then take this course. or If you want to start your own startup by building your own websites and web apps. or If you are a complete beginner then this course will be everything you need to become a Python professional or If you are a seasoned programmer wanting to switch to Python then this is the quickest way. Learn through coding projects. or If you are an intermediate Python programmer then you know 100 days of code challenges will help you level up.
Learn More About 100 Days of Code: The Complete Python Pro Bootcamp
What You Will Learn
- You will master the Python programming language by building 100 unique projects over 100 days.
- You will learn automation, game, app and web development, data science and machine learning all using Python.
- You will be able to program in Python professionally
- You will learn Selenium, Beautiful Soup, Request, Flask, Pandas, NumPy, Scikit Learn, Plotly, and Matplotlib.
- Create a portfolio of 100 Python projects to apply for developer jobs
- Be able to build fully fledged websites and web apps with Python
- Be able to use Python for data science and machine learning
- Build games like Blackjack, Pong and Snake using Python
- Build GUIs and Desktop applications with Python
2. Complete Data Science,Machine Learning,DL,NLP Bootcamp
Instructor: Krish Naik
Master the theory, practice,and math behind Data Science,Machine Learning,Deep Learning,NLP with end to end projects
Course Highlights:
- Rating: 4.56 ⭐ (9984 reviews)
- Students Enrolled: 62641
- Course Length: 356914 hours
- Number of Lectures: 442
- Number of Quizzes: 20
Complete Data Science,Machine Learning,DL,NLP Bootcamp, has an average rating of 4.56, with 442 lectures, 20 quizzes, based on 9984 reviews, and has 62641 subscribers.
You will learn about Master foundational and advanced Machine Learning and NLP concepts. Apply theoretical and practical knowledge to real-world projects using Machine learning,NLP And MLOPS Understand and implement mathematical principles behind ML algorithms. Develop and optimize ML models using industry-standard tools and techniques. Understand The Core intuition of Deep Learning such as optimizers,loss functions,neural networks and cnn This course is ideal for individuals who are Aspiring data scientists and machine learning enthusiasts. or Students and professionals looking to enhance their ML and NLP skills. or Beginners with a basic understanding of programming and mathematics. or Anyone interested in understanding and applying machine learning and NLP techniques from scratch to advanced levels. or Beginners Python Developer who wants to get into the Data Science field It is particularly useful for Aspiring data scientists and machine learning enthusiasts. or Students and professionals looking to enhance their ML and NLP skills. or Beginners with a basic understanding of programming and mathematics. or Anyone interested in understanding and applying machine learning and NLP techniques from scratch to advanced levels. or Beginners Python Developer who wants to get into the Data Science field.
Learn More About Complete Data Science,Machine Learning,DL,NLP Bootcamp
What You Will Learn
- Master foundational and advanced Machine Learning and NLP concepts.
- Apply theoretical and practical knowledge to real-world projects using Machine learning,NLP And MLOPS
- Understand and implement mathematical principles behind ML algorithms.
- Develop and optimize ML models using industry-standard tools and techniques.
- Understand The Core intuition of Deep Learning such as optimizers,loss functions,neural networks and cnn
1. The Data Science Course: Complete Data Science Bootcamp 2025
Instructor: 365 Careers
Complete Data Science Training: Math, Statistics, Python, Advanced Statistics in Python, Machine and Deep Learning
Course Highlights:
- Rating: 4.59 ⭐ (150361 reviews)
- Students Enrolled: 744484
- Course Length: 112585 hours
- Number of Lectures: 553
- Number of Quizzes: 277
The Data Science Course: Complete Data Science Bootcamp 2025, has an average rating of 4.59, with 553 lectures, 277 quizzes, based on 150361 reviews, and has 744484 subscribers.
You will learn about 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 This course is ideal for individuals who are You should take this course if you want to become a Data Scientist or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills It is particularly useful for You should take this course if you want to become a Data Scientist or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills.
Learn More About The Data Science Course: Complete Data Science Bootcamp 2025
What You Will 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
Note: This post contains affiliate links. We may receive a commission for purchases made through these links.
- Best Investing Courses to Learn in March 2025
- Best Personal Finance Courses to Learn in March 2025
- Best Health And Wellness Courses to Learn in March 2025
- Best Chatgpt And Ai Tools Courses to Learn in March 2025
- Best Virtual Reality Courses to Learn in March 2025
- Best Augmented Reality Courses to Learn in March 2025
- Best Blockchain Development Courses to Learn in March 2025
- Best Unity Game Development Courses to Learn in March 2025
- Best Artificial Intelligence Courses to Learn in March 2025
- Best Flutter Development Courses to Learn in March 2025
- Best Docker Kubernetes Courses to Learn in March 2025
- Best Business Analytics Courses to Learn in March 2025
- Best Excel Vba Courses to Learn in March 2025
- Best Devops Courses to Learn in March 2025
- Best Angular Courses to Learn in March 2025
- Best Node Js Development Courses to Learn in March 2025
- Best React Js Courses to Learn in March 2025
- Best Cyber Security Courses to Learn in March 2025
- Best Machine Learning Courses to Learn in March 2025
- Best Ethical Hacking Courses to Learn in March 2025
