What you’ll learn in The Data Science Course 2021: Complete Data Science Bootcamp
- The course equips you with all of the tools you’ll need to work as a data scientist.
- Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, and Deep learning with TensorFlow are some of the most in-demand data science skills.
- Show your knowledge of data science to impress your interviewers.
- Pre-processing data is a skill that should be learned.
- Understand the mathematics behind Machine Learning (which other courses do not cover!)
- Learn how to code in Python and apply it to statistical analysis.
- Python allows you to carry out linear and logistic regressions.
- Cluster and factor analysis should be carried out.
- Using NumPy, statsmodels, and scikit-learn, be able to create Machine Learning algorithms in Python.
- Use your knowledge to solve real-world problems.
- Develop a business intuition while coding and solving tasks with big data using state-of-the-art Deep Learning frameworks such as Google’s TensorFlow
- Deep neural networks have a lot of power.
- Study underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters can improve performance in Machine Learning algorithms.
- Warm up your fingers because you’ll be eager to put what you’ve learned here to use in a variety of situations.
- We will begin from the very beginning, with no prior experience required.
- You must first install Anaconda, which we will walk you through step by step.
- Excel 2003, 2010, 2013, 2021 , or 365 are some of the versions of Microsoft Excel that are available.
The issue at hand
Because data scientists are one of the best-suited professions for this century, being digital, programming-oriented, and analytical, it’s no surprise that demand for them has been on the rise.
However, demand has been high, and obtaining the skills required to work as a data scientist has proven difficult.
Universities have been slow to develop specialized data science programs (not to mention that those that do exist are costly and time-consuming).
The majority of online courses concentrate on a single topic, making it difficult to see how the skill they teach fits into the bigger picture.
Data science is a multidisciplinary field that covers many different topics.
Each of these topics builds on the previous ones, and if you don’t learn them in the correct order, you risk getting lost along the way. For example, applying Machine Learning techniques without first understanding the underlying Mathematics can be difficult, and learning regression analysis in Python without first understanding what a regression is can be overwhelming.
We believe this is the first training program to address the most significant barrier to entry into the field of data science: having all of the necessary resources in one location.
The course teaches you everything you need to know to become a data scientist at a fraction of the cost of traditional programs (not to mention the time you’ll save).
1. Data and Data Science: A Beginner’s Guide
We all know that big data, business intelligence, business analytics, machine learning, and artificial intelligence are buzzwords in the field of data science, but what exactly do they mean?
Why should you learn it? As a candidate data scientist, you’ll need to know the ins and outs of each of these areas and be able to recognize the best approach to solving a problem. This ‘Intro to Data and Data Science’ will give you a comprehensive look at all of these buzzwords and where they fit into the realm of data science.
The first step in doing data science is to learn the tools; you must first see the big picture before diving into the details.
We look at calculus and linear algebra in particular because they are the subfields on which data science is built.
If you want to understand advanced machine learning algorithms, you’ll need to know calculus and linear algebra.
3. Informational data
Before you can become a scientist, you must first think like one, and statistics teaches you how to frame problems as hypotheses and how to test them, just like a scientist.
This course not only provides you with the necessary tools, but also teaches you how to use them. Statistics teaches you how to think like a scientist.
Python is number four.
Python is a relatively new programming language that, unlike R, is a general-purpose programming language that can be used to do anything. Web applications, computer games, and data science are just a few of its capabilities, which is why it has managed to disrupt many disciplines in such a short time.
Python is a must-have programming language for developing, implementing, and deploying machine learning models using powerful frameworks like scikit-learn and TensorFlow.
Data scientists must not only deal with data and solve data-driven problems; they must also be able to persuade company executives of the right decisions to make. These executives may not be well-versed in data science, so the data scientist must be able to present and visualize the data’s story in a way that they can understand. That’s where Tableau comes in – and we’ll help you become an expert story teller using the leading visualisation software in business intelligence.
To communicate complex results to non-technical decision makers, a data scientist uses business intelligence tools such as Tableau.
6. Statistical Methods
Regressions, clustering, and factor analysis are all statistical methods that were invented before machine learning, but they are now all performed by machine learning to provide predictions with unparalleled accuracy.
Predictive modeling is at the heart of data science, and this section on ‘advance statistics’ will help you master these techniques.
Deep learning is the final section of the program, and it is what each section has been leading up to. The ability to use machine and deep learning in their work is often what distinguishes a data scientist from a data analyst, and this section covers all common machine learning and deep learning methods with TensorFlow.
Machine learning is everywhere; companies like Facebook, Google, and Amazon have been using self-learning machines for years, and now it’s your turn to command them.
***How it works***
You will learn how to become a data scientist from the ground up, with no risk to you. The course content is excellent, and we are confident you will enjoy it.
Who this course is for:
- You should take this course if you want to become a Data Scientist or if you want to learn about the field
- This course is for you if you want a great career
- The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
|File Name :||The Data Science Course 2021: Complete Data Science Bootcamp Free Download|
|Genre / Category:||Data Science|
|File Size :||2.87 gb|
|Publisher :||365 Careers|
|Updated and Published:||24 Oct,2021|