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Build your mathematics and statistics foundations strongly and ensure your Data science fundamentals are in place!
What you’ll learn
You will gain a firm foothold of the fundamentals of Data Science. The course provides the entire toolbox you need to become a data scientist.
You will understand the mathematics and statistics behind Machine Learning
You will understanding the Octagonal Technical Facets of Data Science
You will start coding in Python and learn how to use it for statistical analysis
You will improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
You will unfold the power of deep neural networks
You will carry out cluster and factor analysis
You will learn how to pre-process data
Impress interviewers by showing an understanding of the data science field
Apply your skills to real-life business cases
What will I Learn and Apply post-program:
We build your foundation by going through the basics of Mathematics, Statistics and Machine Learning using our foundation training program on Data Science – DS1 Module:
In our DS1 Module You will Learn:
1)Descriptive & Inferential Statistics
4)Data Distributions – Discrete/Continuous
5)Matrix Algebra, Coordinate geometry & Calculus
6)CRISP-DM Framework 7)Machine Learning – Part 1
8)Python Programming – Adv
9)Simple & Multiple Linear regression with case studies
A Data Scientist dons many hats in his/her workplace. Not only are Data Scientists responsible for business analytics, but they are also involved in building data products and software platforms, along with developing visualizations and machine learning algorithms
Data Analytics career prospects depend not only on how good are you with programming —equally important is the ability to influence companies to take action. As you work for an organization, you will improve your communication skills.
A Data Analyst interprets data and turns it into information that can offer ways to improve a business, thus affecting business decisions. Data Analysts gather information from various sources and interpret patterns and trends – as such a Data Analyst job description should highlight the analytical nature of the role.
Key skills for a data analyst
- A high level of mathematical ability.
- Programming languages, such as SQL, Oracle, and Python.
- The ability to analyze, model and interpret data.
- Problem-solving skills.
- A methodical and logical approach.
- The ability to plan work and meet deadlines.
- Accuracy and attention to detail.
R for Data Science:
This session is for “R for Data Science”. We will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it. In this session, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualizing and exploring data.
Why learn it?
Machine learning is everywhere. Companies like Facebook, Google, and Amazon have been using machines that can learn on their own for years. Now is the time for you to control the machines.
***What you get***
- Active Q&A support
- All the knowledge to get hired as a data scientist
- A community of data science learners
- A certificate of completion
- Access to future updates
- Solve real-life business cases that will get you the job
You will become a data scientist from scratch
Why wait? Every day is a missed opportunity.
Click the “Buy Now” button and become a part of our data scientist program today.
- The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
- You should take this course if you want to become a Data Scientist or if you want to learn about the field
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