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Data Science Mastery Course

person icon AKHIL VYDYULA

4.7

Data Science Mastery Course

Master the skills needed to become a Data Scientist, with hands-on projects in Python, Machine Learning

updated on icon Updated on Mar, 2025

language icon Language - English

person icon AKHIL VYDYULA

category icon IT and Software ,Other IT and Software,Machine Learning

Lectures -95

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4.7

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Course Description

Welcome to the Complete Data Scientist & Machine Learning BootCamp Course, your one-stop guide to mastering the foundational skills required to excel in data science.

Whether you're a beginner or looking to refine your knowledge, this 40+ hour comprehensive course will take you from zero experience to full proficiency. Here’s what makes this course stand out:

  • Top-Tier Instruction: Learn directly from the lead instructor at PwC, India's top programming boot camp, where thousands have been trained.
  • Cutting-Edge Tools: You'll be equipped with the same technologies used by data scientists at renowned companies like Google, Amazon, and Netflix.
  • Real-World Projects: Dive into practical, industry-relevant projects that mirror the real work of data scientists.

Why this Course?

This course was meticulously crafted over three years with input from industry professionals and researchers. As a result, it doesn’t just cover theory; you'll gain hands-on experience with tools and techniques that are essential in the industry. From foundational concepts to advanced techniques, every lesson has been designed to take you closer to mastery.

To date, over 10,000+ students have successfully transitioned into data science roles or started their own tech ventures after taking this course.

What You’ll Learn:

Machine Learning Topics:

  • Regression: Dive deep into Linear Regression, Support Vector Machines (SVR), Decision Trees, and Random Forests.
  • Clustering: Master K-Means and Hierarchical Clustering techniques.
  • Classification: Explore algorithms like Logistic Regression, Kernel SVM, Naive Bayes, and Random Forest Classification.
  • NLP (Natural Language Processing): Learn Bag-of-Words and other essential NLP algorithms.

Deep Learning Topics:

  • Neural Networks: Build Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), and work with advanced models like VGG16.
  • Transfer Learning: Leverage pre-trained models and deploy them in Flask-based web applications.

Python Programming: From basics to advanced, you'll gain expertise in:

  • Data types, variables, and string manipulation
  • Loops, conditionals, and control flow
  • Functions, generators, context managers, and error-handling

Power BI Mastery:

  • Learn the essentials of Power BI: from importing data to creating insightful dashboards and reports.
  • Explore DAX functions and use visuals to present data like a pro.

Real-World Focus

Throughout the course, you’ll apply what you’ve learned to real-world projects, gaining hands-on experience in solving complex problems. By the end, you'll be fully equipped to handle any data science project, confident in your Python programming, machine learning, and Power BI skills.

What’s Included:

  • 178+ HD Video Lectures
  • 30+ Coding Challenges & Exercises
  • Complete Data Science Projects
  • Exclusive Programming Resources & Cheatsheets
  • Our Best-Selling eBook: "12 Rules to Learn to Code"

With over $12,000 worth of content and materials, this course offers the most in-depth learning experience for aspiring data scientists at a fraction of the cost.

Enroll today and start your journey to becoming a data science expert!

Goals

  • Regression: Dive deep into Linear Regression, Support Vector Machines (SVR), Decision Trees, and Random Forests.
  • Clustering: Master K-Means and Hierarchical Clustering techniques.
  • Classification: Explore algorithms like Logistic Regression, Kernel SVM, Naive Bayes, and Random Forest Classification.
  • NLP (Natural Language Processing): Learn Bag-of-Words and other essential NLP algorithms.
  • Neural Networks: Build Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), and work with advanced models like VGG16.
  • Transfer Learning: Leverage pre-trained models and deploy them in Flask-based web applications.
  • Data types, variables, and string manipulation
  • Loops, conditionals, and control flow
  • Functions, generators, context managers, and error-handling

Prerequisites

None
Data Science Mastery Course

Curriculum

Check out the detailed breakdown of what’s inside the course

Instructor Details

AKHIL VYDYULA

AKHIL VYDYULA

Data Scientist | Data & Analytics Specialist | Entrepreneur

Hello, I'm Akhil, a Senior Data Scientist at PwC specializing in the Advisory Consulting practice with a focus on Data and Analytics.

My career journey has provided me with the opportunity to delve into various aspects of data analysis and modelling, particularly within the BFSI sector, where I've managed the full lifecycle of development and execution.


I possess a diverse skill set that includes data wrangling, feature engineering, algorithm development, and model implementation. My expertise lies in leveraging advanced data mining techniques, such as statistical analysis, hypothesis testing, regression analysis, and both unsupervised and supervised machine learning, to uncover valuable insights and drive data-informed decisions. I'm especially passionate about risk identification through decision models, and I've honed my skills in machine learning algorithms, data/text mining, and data visualization to tackle these challenges effectively.


Currently, I am deeply involved in an exciting Amazon cloud project, focusing on the end-to-end development of ETL processes. I write ETL code using PySpark/Spark SQL to extract data from S3 buckets, perform necessary transformations, and execute scripts via EMR services. The processed data is then loaded into Postgres SQL (RDS/Redshift) in full, incremental, and live modes. To streamline operations, I’ve automated this process by setting up jobs in Step Functions, which trigger EMR instances in a specified sequence and provide execution status notifications. These Step Functions are scheduled through EventBridge rules.


Moreover, I've extensively utilized AWS Glue to replicate source data from on-premises systems to raw-layer S3 buckets using AWS DMS services. One of my key strengths is understanding the intricacies of data and applying precise transformations to convert data from multiple tables into key-value pairs. I’ve also optimized stored procedures in Postgres SQL to efficiently perform second-level transformations, joining multiple tables and loading the data into final tables.


I am passionate about harnessing the power of data to generate actionable insights and improve business outcomes. If you share this passion or are interested in collaborating on data-driven projects, I would love to connect. Let’s explore the endless possibilities that data analytics can offer!

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