Full Stack Data Science & Machine Learning BootCamp Course
What you'll learn
- Build a real-world portfolio: Create multiple data science projects to demonstrate your skills to potential employers.
- Master data visualization: Design clear, insightful charts (bar, line, scatter, histogram, etc.) and use visualization techniques to explore and present large d
- Develop deep learning skills: Construct, train, and deploy neural networks for tasks like image recognition and data classification.
- Apply core algorithms: Use common data science and machine learning algorithms on real projects (for example, classifying mushrooms or analyzing images).
- Use modern tools: Learn to work with essential data science tools and libraries (TensorFlow, NumPy, Matplotlib, Pandas, etc.) to process data and build models.
- Understand how to use the latest tools in data science, including Tensorflow, Matplotlib, Numpy and many more
- Computer with internet: Just have a Windows or Mac computer and internet access; that’s all you need to get started.
Requirements
- No prior experience required: You do not need any programming, calculus, or statistics background. We start from the very basics.
- Free tools only: All course projects use free, open-source software—no paid tools needed.
- No statistics knowledge required! I’ll teach you everything you need to know.
- Also, no paid software required - all projects use free and open source software
- All you need is Mac or PC computer with access to the internet
Description
Welcome to the Full Stack Data Science & Machine Learning BootCamp Course, the only course you need to learn Foundation skills and get into data science.
At over 40+ hours, this Python course is without a doubt the most comprehensive data science and machine learning course available online. Even if you have zero programming experience, this course will take you from beginner to mastery. Here's why:
The course is taught by the lead instructor at the PwC, India's leading in-person programming bootcamp.
In the course, you'll be learning the latest tools and technologies that are used by data scientists at Google, Amazon, or Netflix.
This course doesn't cut any corners, there are beautiful animated explanation videos and real-world projects to build.
The curriculum was developed over a period of three years together with industry professionals, researchers and student testing and feedback.
To date, I’ve taught over 10000+ students how to code and many have gone on to change their lives by getting jobs in the industry or starting their own tech startup.
You'll save yourself over $12,000 by enrolling, but get access to the same teaching materials and learn from the same instructor and curriculum as our in-person programming bootcamp.
We'll take you step-by-step through video tutorials and teach you everything you need to know to succeed as a data scientist and machine learning professional.
The course includes over 40+ hours of HD video tutorials and builds your programming knowledge while solving real-world problems.
In the curriculum, we cover a large number of important data science and machine learning topics, such as:
MACHINE LEARNING -
Regression: Simple Linear Regression, , SVR, Decision Tree , Random Forest,
Clustering: K-Means, Hierarchical Clustering Algorithms
Classification: Logistic Regression, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
Natural Language Processing: Bag-of-words model and algorithms for NLP
DEEP LEARNING -
Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Long short term Memory, Vgg16 , Transfer learning, Web Based Flask Application.
Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.
By the end of this course, you will be fluently programming in Python and be ready to tackle any data science project. We’ll be covering all of these Python programming concepts:
PYTHON -
Data Types and Variables
String Manipulation
Functions
Objects
Lists, Tuples and Dictionaries
Loops and Iterators
Conditionals and Control Flow
Generator Functions
Context Managers and Name Scoping
Error Handling
Power BI -
What is Power BI and why you should be using it.
To import CSV and Excel files into Power BI Desktop.
How to use Merge Queries to fetch data from other queries.
How to create relationships between the different tables of the data model.
All about DAX including using the COUTROWS, CALCULATE, and SAMEPERIODLASTYEAR functions.
All about using the card visual to create summary information.
How to use other visuals such as clustered column charts, maps, and trend graphs.
How to use Slicers to filter your reports.
How to use themes to format your reports quickly and consistently.
How to edit the interactions between your visualizations and filter at visualization, page, and report level.
By working through real-world projects you get to understand the entire workflow of a data scientist which is incredibly valuable to a potential employer.
Sign up today, and look forward to:
178+ HD Video Lectures
30+ Code Challenges and Exercises
Fully Fledged Data Science and Machine Learning Projects
Programming Resources and Cheatsheets
Our best selling 12 Rules to Learn to Code eBook
$12,000+ data science & machine learning bootcamp course materials and curriculum
Who this course is for:
- Complete beginners: Anyone new to data science or machine learning looking for a comprehensive, step-by-step introduction.
- Career changers: Programmers and tech professionals who want to quickly learn data science workflows and tools.
- Aspiring ML engineers: Learners interested in building and applying machine learning and deep learning models.
- The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
- Portfolio builders: Students who want hands-on experience and to create projects they can showcase in job interviews.
Instructor
- 4.0 Instructor Rating
- 1,139 Reviews
- 70,807 Students
- 46 Courses
Hello, I'm Akhil Vydyula — Lead Data Engineer at Publicis Sapient, and Former Senior Data Scientist at PwC.
With over 5 years of rich industry experience and a strong focus on the BFSI sector, I’ve led and delivered end-to-end data and analytics solutions that power strategic decisions and transform business outcomes.
At Publicis Sapient, I currently lead complex data engineering initiatives, leveraging my deep expertise in cloud-native platforms like AWS to architect robust, scalable data pipelines. My work spans across developing and optimizing ETL workflows using PySpark and Spark SQL, orchestrating data flows via EMR, Step Functions, and EventBridge, and driving real-time and batch data processing into PostgreSQL (RDS/Redshift) environments. I've also implemented AWS Glue and DMS to seamlessly replicate and transform large-scale on-premise data into cloud-native formats.
Previously, at PwC, I specialized in advanced analytics and machine learning within the Advisory Consulting practice. I’ve built and deployed predictive models using statistical analysis, regression, classification, clustering, and text mining—particularly for risk identification and decision modeling. My passion lies in transforming raw data into actionable insights through effective data storytelling and visualization.
In parallel to my corporate career, I bring over 5 years of teaching experience, mentoring hundreds of aspiring data professionals. I’m deeply committed to helping students break into the data industry by translating real-world challenges into practical learning experiences.
Whether it's building data pipelines, uncovering business insights, or shaping the next generation of data talent, I thrive at the intersection of technology, strategy, and impact.
Let’s connect if you're passionate about data, eager to learn, or looking to collaborate on meaningful, data-driven initiatives.