Best Data Science Courses
Choosing the best data science course is crucial for a successful career in this rapidly evolving field. Start by assessing your skill level and career goals. Beginners may benefit from courses that cover fundamental concepts, such as Python programming, statistics, and machine learning basics. Intermediate learners might focus on specialized areas like natural language processing or computer vision. Advanced practitioners may seek courses in deep learning or advanced data manipulation techniques.
Consider the course format: online platforms like Udemy ,Coursera, edX, and Udacity offer flexibility, while university programs provide in-depth knowledge. Look for courses with hands-on projects and real-world applications to enhance practical skills. Additionally, check for industry-recognized certifications and feedback from previous participants. Finally, explore free resources and trial versions to ensure the course aligns with your learning style and preferences. Making a well-informed decision will set you on the path to becoming a proficient data scientist.
Here we listed Best Free & Paid Data Science Courses which will help you learn Data Science, and are suitable for beginners, intermediate learners as well as experts.
What is Data Science ?
What you’ll learn
- How to define Data Science ?
- What are the components of Data Science ?
- Entry level overview of Data Science components
The Data Science Course: Complete Data Science Bootcamp 2023 -31 Hours
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
Complete Machine Learning & Data Science Bootcamp 2023 -43.5 hrs
- The topics covered in this course are:
- – Data Exploration and Visualizations
- – Neural Networks and Deep Learning
- – Model Evaluation and Analysis
- – Python 3
- – Tensorflow 2.0
- – Numpy
- – Scikit-Learn
- – Data Science and Machine Learning Projects and Workflows
- – Data Visualization in Python with MatPlotLib and Seaborn
- – Transfer Learning
- – Image recognition and classification
- – Train/Test and cross validation
- – Supervised Learning: Classification, Regression and Time Series
- – Decision Trees and Random Forests
- – Ensemble Learning
- – Hyperparameter Tuning
- – Using Pandas Data Frames to solve complex tasks
- – Use Pandas to handle CSV Files
- – Deep Learning / Neural Networks with TensorFlow 2.0 and Keras
- – Using Kaggle and entering Machine Learning competitions
- – How to present your findings and impress your boss
- – How to clean and prepare your data for analysis
- – K Nearest Neighbours
- – Support Vector Machines
- – Regression analysis (Linear Regression/Polynomial Regression)
- – How Hadoop, Apache Spark, Kafka, and Apache Flink are used
- – Setting up your environment with Conda, MiniConda, and Jupyter Notebooks
- – Using GPUs with Google Colab
Data Science A-Z™: Hands-On Exercises & ChatGPT Bonus [2023]
This course will give you a full overview of the Data Science journey. Upon completing this course you will know:
- How to clean and prepare your data for analysis
- How to perform basic visualisation of your data
- How to model your data
- How to curve-fit your data
- And finally, how to present your findings and wow the audience
This course will give you so much practical exercises that real world will seem like a piece of cake when you graduate this class. This course has homework exercises that are so thought provoking and challenging that you will want to cry… But you won’t give up! You will crush it. In this course you will develop a good understanding of the following tools:
- SQL
- SSIS
- Tableau
- Gretl
Enroll Now
Foundations of Data Science & Machine Learning
What you’ll learn
- Learn the essentials – the three main pillars of data science and ML – Programming, Math, and Statistics.
- Everything from basic data structures to data extraction using python programming. Learn to work with data libraries: NumPy, Pandas, Matplotlib, and Seaborn.
- How linear algebra and calculus underpin the training of ML models.
- How Statistics enables you to describe data and quantify uncertainty in an experiment.
- Cover all pre-requisites and pre-work before starting any Google’s(or any) data science or ML program.
- Build models from scratch, learn the math behind, program
Data Science Ethics
What you’ll learn
- This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data
- You will examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems
Duration: Approx. 17 hours
Data Science: Machine Learning
What you’ll learn
- The basics of machine learning
- How to perform cross-validation to avoid overtraining
- Several popular machine learning algorithms
- How to build a recommendation system
- What is regularization and why it is useful?
IBM Data Science Professional Certificate
What you’ll learn
- Create and access a database instance on cloud
- Write basic SQL statements: CREATE, DROP, SELECT, INSERT, UPDATE, DELETE
- Filter, sort, group results, use built-in functions, access multiple tables
- Access databases from Jupyter using Python and work with real world datasets
Duration: Approx. 3 months {13 hours/week}
Rating: 4.6 (107,127 ratings) out of 5
Trainer: IBM
Applied Data Science with Python Specialization
What you’ll learn
- Conduct an inferential statistical analysis
- Discern whether a data visualization is good or bad
- Enhance a data analysis with applied machine learning
- Analyze the connectivity of a social network
Data Science Specialization -10 course series with Certification
What you’ll learn
- Use R to clean, analyze, and visualize data.
- Navigate the entire data science pipeline from data acquisition to publication.
- Use GitHub to manage data science projects.
- Perform regression analysis, least squares and inference using regression models.
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
Choose a course aligned with your goals, and remember, consistent practice is key to mastering the dynamic field of data science.
How to Enroll 10 Best Data Science Courses – Learn Data Science online course?
How many members can access this course with a coupon?
10 Best Data Science Courses – Learn Data Science online Course coupon is limited to the first 1,000 enrollments. Click 'Enroll Now' to secure your spot and dive into this course on Udemy before it reaches its enrollment limits!
