Full Stack Data Science & Machine Learning BootCamp Course

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