Hello everyone! I am someone who has made a transition to the Data Science field with much aspiration to work in the industry. About the course: it is totally worth your money and your time. The project through which you will get hands-on experience is very carefully designed and has a practical use case. I got good insights on how things work in the industry. About the instructor: to say the least, Dhaval Sir is very experienced and is a fantastic teacher. He has been very patient throughout the entire course and has put much effort in each of the lectures. Also, the support team is very nice; you will get responses and explanations for your doubts.
Senior Research Fellow
I would give this course 5/5 rating. Dhaval has impeccable teaching abilities, and the exercises and quizzes for the course are thoughtfully structured for every chapter. The AtliQo project provided us with an extensive understanding of every concept we had learned in course. I particularly like the AtliQo project's overall story telling, which included discussions about the realities of work culture, business meetings, and DS responsibility. Dhaval sir is creative and the code basics team is doing exellent job. I am grateful to Dhaval, Hemanand, and the crew. Thanks, Nitin.
Senior Application Consultant
I have a 10+ years of experience in Software Quality Assurance but want to transition to a Product Management field backed by Data Science knowledge. Data Science is such a huge field in itself it can be overwhelming. Dhaval sir's Data Science roadmap gives you the required strategy for getting yourself upto speed. It gives you the ammunition to conquer the Data Science war (if I may put it in those words). But what after you get the ammunition, you need to know how to use the ammunition as well. These course lectures on Python, Maths & Statistics (I am sure the others are also as well) are so lucidly explained in simple words and real time Jupyter notebook python coding examples, it really gives you the solid foundational knowledge. Needless to say, the quizzes & exercises helps you get a solid grip on the concept. I hope to complete the roadmap ASAP and transition to my aspired field.
All the courses of Codebasics are highly recommended for all who wants to learn & grow in the data field.
Software Quality Engineering Lead
Just finished this awesome course! It was clear, engaging, and packed with useful info. The lessons were short and easy to understand, making learning fun and efficient. Highly recommend to anyone looking to improve their skills!
"Math and Stats for Data Science" by the Codebasics team is an exceptional course that provides a robust framework for mastering the mathematical and statistical concepts crucial for success in the field of data science. As someone who embarked on this educational journey with a thirst for knowledge and a desire to bolster my quantitative skills, I can attest to the efficacy and value of this course.
The course begins with a solid foundation, covering fundamental mathematical concepts such as algebra, calculus, and linear algebra. Each topic is presented in a clear and concise manner, with ample examples and explanations that cater to learners of all levels. Whether you're a newcomer to the world of data science or a seasoned professional looking to sharpen your mathematical acumen, the course offers something for everyone.
One of the standout features of this course is its emphasis on real-world applications. The Codebasics team does an exemplary job of bridging the gap between theory and practice, demonstrating how mathematical and statistical principles are used to solve practical problems in data science. From regression analysis to hypothesis testing, each concept is contextualized within the realm of data analysis, providing learners with valuable insights into its relevance and utility.
The instructors at Codebasics are truly exceptional. Their passion for teaching shines through in every lecture, as they guide learners through complex mathematical concepts with patience and clarity. Moreover, the use of interactive quizzes and coding exercises fosters active engagement, allowing learners to reinforce their understanding through hands-on practice.
Another commendable aspect of this course is its comprehensive coverage of statistical techniques. From probability theory to inferential statistics, the curriculum is designed to equip learners with the analytical tools necessary for extracting meaningful insights from data. Whether you're analyzing financial trends or predicting customer behavior, the statistical knowledge gained from this course will serve as a valuable asset in your data science toolkit.
Furthermore, the course is supplemented with a vibrant community of learners who provide support, encouragement, and camaraderie throughout the learning journey. Whether you're seeking clarification on a difficult concept or sharing insights from your own experiences, the Codebasics community is a valuable resource for collaboration and knowledge exchange.
In conclusion, "Math and Stats for Data Science" by the Codebasics team is a must-have resource for anyone looking to excel in the field of data science. With its comprehensive curriculum, expert instruction, and practical approach, this course equips learners with the mathematical and statistical foundations necessary to thrive in a data-driven world. Whether you're embarking on a new career path or seeking to enhance your existing skill set, this course is sure to exceed your expectations and unlock new opportunities for growth and success.
Lead Data Engineer
93 Lectures | 11hr : 34min
17 Lectures
Descriptive vs. Inferential Statistics
Measures of Central Tendency: Mean, Median, Mode
Percentile
Analysis: Shoe Sales (Using Mean, Median, Percentile)
Quiz
Exercise
Measures of Dispersion: Range, IQR
Box or Whisker Plot
Outlier Treatment Using IQR and Box Plot
Quiz
Exercise
Measures of Dispersion: Variance and Standard Deviation
Analysis: Stock Returns Volatility (Using Variance and Std Dev)
Correlation
Correlation vs Causation
Quiz
Exercise
21 Lectures
Data Validation Of Acquired Data
Data Understanding, MySQL Setup
Data Import in Jupyter Notebook
Data Cleaning: Handle NULL Values (Annual Income)
Data Cleaning: Treat Outliers (Annual Income)
Data Visualization: Annual Income
Exercise: Treat Outliers in Age Column
Exercise Solution: Treat Outliers in Age Column
Data Visualization: Age, Gender, Location
Peter’s Nightmare
Data Cleaning: Credit Score Table - Part 1
Data Cleaning: Credit Score Table - Part 2
Correlation among Credit Profile Variables
Exercise: Handle NULL Values in Transactions Table
Exercise Solution: Handle NULL Values in Transactions Table
Peter’s Confusion: IQR or Std Dev?
Data Cleaning: Treat Outliers using IQR (Transaction Amount)
Data Visualization: Transactions Table
Finalize the Target Group
Phase 1 Feedback Meeting With Stakeholders
Get Ready For Phase 2
18 Lectures
Null vs Alternate Hypothesis
Z Test, Rejection Region
Housing Inflation Test: Rejection Region
Quiz
Exercise
p-Value
Housing Inflation Test: p-Value
Quiz
Exercise
One-Tailed vs Two-Tailed Test
Type 1 and Type 2 Errors
Quiz
Statistical Power & Effect Size
A/B Testing
A/B Testing Using Z Test
A/B Testing: Drug Trial
Quiz
Exercise
This course simplifies learning Math and Statistics through project-based learning with a real dataset, focusing on practical data science applications. With engaging storytelling, simple explanations, and interactive exercises, including quizzes, ensures a comprehensive and accessible learning experience. A certificate upon completion further validates your learning journey.
This 'Math & Statistics' course is designed for absolute beginners, so you don't need any specific skills other than basic familiarity with computers. It's the perfect starting point for anyone looking to embark on a data science journey.
Most of the courses available on the internet teach you how to build x & y without any business context and do not prepare you for real-world problem-solving. However, our 'Math & Statistics' course offers a unique experience in which you will learn by solving real-life use cases in an imaginary company called AtliQo Bank. The tutorials are easy to understand, featuring elements of fun to keep the learning process engaging.
Yes. Absolutely you can mention AtliQo Bank project experience in your resume with the relevant skills that you will learn from this course.
Don't worry. Many videos in this 'Math & Statistics' course are free, allowing you to gauge the quality of teaching before making an investment. Dhaval Patel, the course instructor, runs a popular data science YouTube channel called Codebasics. There, you can watch his videos and read comments to get an idea of his teaching style.
In the early stages of the course, we introduce fundamental concepts using a variety of small datasets. As the course progresses, we engage with the 'AtliQo Credit Card' data which centers around a dataset from the fictional AtliQo Bank. This project provides a hands-on experience in data validation, cleaning, and visualization, reflecting a realistic scenario where the bank aims to enhance its credit card market penetration. This dataset contains over half a million records.
We have an active Discord server where you can post your questions. You can expect to receive a response in a reasonable timeframe.
The 'Math & Statistics' course consists of 11 hours and 34 minutes of on-demand video content.
No, this course is not part of our data analytics curriculum. Nevertheless, mastering the concepts of mathematics and statistics will significantly enhance your analytical ability.
No. This course is not part of the Data Analytics Bootcamp.
You receive a ‘Certificate of Completion’ signed and addressed personally by me, your guide and mentor – Dhaval Patel
Add and Share this certificate with your Resume/ CV or on your LinkedIn Profile
This course uses a project-based learning approach to teach you Python using two real-life projects (1) Hospitality domain data analysis and (2) Medical data extraction. Learning Python programming through projects helps you understand real-life applications of this awesome programming language. You will also have two solid projects that you can add to your resume and you work on end-to-end implementation. Total beginners, as well as people familiar with the language, will benefit from this Python course.
Beginners to Advanced SQL course for those preparing for a data career (data analyst, data scientist, or data engineer). This course is carefully curated to simulate real-time organizational experience to prepare you for the current job market and at the same time provides you with an ultimate learning experience through a storytelling mode that you would see in movies.