The Data Science Course 2022: Complete Data Science Bootcamp (

This near-30-hour course delves deep into the concepts and methods of data science. It starts with the basics and teaches the math, graphical methods and coding necessary to break into data science.

Created by: 365 Careers

Produced in 2022

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Overall Score : 92 / 100

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Course Description

data science Awards Sponsored

The Problem
Data scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace.
However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist.
And how can you do that?
Universities have been slow at creating specialized data science programs. (not to mention that the ones that exist are very expensive and time consuming)
Most online courses focus on a specific topic and it is difficult to understand how the skill they teach fit in the complete picture
The Solution
Data science is a multidisciplinary field. It encompasses a wide range of topics.
  • Understanding of the data science field and the type of analysis carried out
  • Mathematics
  • Statistics
  • Python
  • Applying advanced statistical techniques in Python
  • Data Visualization
  • Machine Learning
  • Deep Learning
Each of these topics builds on the previous ones. And you risk getting lost along the way if you don't acquire these skills in the right order. For example, one would struggle in the application of Machine Learning techniques before understanding the underlying Mathematics. Or, it can be overwhelming to study regression analysis in Python before knowing what a regression is.
So, in an effort to create the most effective, time-efficient, and structured data science training available online, we created The Data Science Course 2019.
We believe this is the first training program that solves the biggest challenge to entering the data science field having all the necessary resources in one place.
Moreover, our focus is to teach topics that flow smoothly and complement each other. 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 amount of time you will save).
The Skills
1. Intro to Data and Data Science
Big data, business intelligence, business analytics, machine learning and artificial intelligence. We know these buzzwords belong to the field of data science but what do they all mean?
Why learn it?As a candidate data scientist, you must understand the ins and outs of each of these areas and recognise the appropriate approach to solving a problem. This Intro to data and data science' will give you a comprehensive look at all these buzzwords and where they fit in the realm of data science.
2. Mathematics
Learning the tools is the first step to doing data science. You must first see the big picture to then examine the parts in detail.
We take a detailed look specifically at calculus and linear algebra as they are the subfields data science relies on.
Why learn it?
Calculus and linear algebra are essential for programming in data science. If you want to understand advanced machine learning algorithms, then you need these skills in your arsenal.
3. Statistics
You need to think like a scientist before you can become a scientist. Statistics trains your mind to frame problems as hypotheses and gives you techniques to test these hypotheses, just like a scientist.
Why learn it?
This course doesn't just give you the tools you need but teaches you how to use them. Statistics trains you to think like a scientist.
4. Python
Python is a relatively new programming language and, unlike R, it is a general-purpose programming language. You can do anything with it! Web applications, computer games and data science are among many of its capabilities. That's why, in a short space of time, it has managed to disrupt many disciplines. Extremely powerful libraries have been developed to enable data manipulation, transformation, and visualisation. Where Python really shines however, is when it deals with machine and deep learning.
Why learn it?
When it comes to developing, implementing, and deploying machine learning models through powerful frameworks such as scikit-learn, TensorFlow, etc, Python is a must have programming language.
5. Tableau
Data scientists don't just need to deal with data and solve data driven problems. They also need to convince company executives of the right decisions to make. These executives may not be well versed in data science, so the data scientist must but be able to present and visualise the data's story in a way they will understand. That's where Tableau comes in and we will help you become an expert story teller using the leading visualisation software in business intelligence and data science.
Why learn it?
A data scientist relies on business intelligence tools like Tableau to communicate complex results to non-technical decision makers.
6. Advanced Statistics
Regressions, clustering, and factor analysis are all disciplines that were invented before machine learning. However, now these statistical methods are all performed through machine learning to provide predictions with unparalleled accuracy. This section will look at these techniques in detail.
Why learn it?
Data science is all about predictive modelling and you can become an expert in these methods through this advance statistics' section.
7. Machine Learning
The final part of the program and what every section has been leading up to is deep learning. Being able to employ machine and deep learning in their work is what often separates a data scientist from a data analyst. This section covers all common machine learning techniques and deep learning methods with TensorFlow.
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***
  • A $1250 data science training program
  • 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
We are happy to offer an unconditional 30-day money back in full guarantee. No risk for you. The content of the course is excellent, and this is a no-brainer for us, as we are certain you will love it.



    • Course is as comprehensive as a first exposure course can be. It covers a little of everything and a lot of some things.
    • Takes very complicated subject matter and makes it just plain easy to understand.
    • Q&A responses are fast and reliable.
    • There is no such thing as a complete data science boot camp. The field is too vast. This is an introduction.
    • Course does a lot more talking about what data science looks like than how to do data science.
    • Course tries to casually pack incredibly deep topics like statistical analysis and deep learning into small modules.

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Instructor Details


365 Careers is the #1 best-selling provider of finance courses on Udemy. The company's courses have been taken by more than 640,000 students in 210 countries. People working at world-class firms like Apple, PayPal, and Citibank have completed 365 Careers trainings.
Currently, the firm focuses on the following topics on Udemy:
1) Finance Finance fundamentals, Financial modeling in Excel, Valuation, Accounting, Capital budgeting, Financial statement analysis (FSA), Investment banking (IB), Leveraged buyout (LBO), Financial planning and analysis (FP&A), Corporate budgeting, applying Python for Finance, Tesla valuation case study, CFA, ACCA, and CPA
2) Data science Statistics, Mathematics, Probability, SQL, Python programming, Python for Finance, Business Intelligence, R, Machine Learning, TensorFlow, Tableau, the integration of SQL and Tableau, the integration of SQL, Python, Tableau, Power BI, Credit Risk Modeling, and Credit Analytics
3) Entrepreneurship Business Strategy, Management and HR Management, Marketing, Decision Making, Negotiation, and Persuasion, Tesla's Strategy and Marketing
4) Office productivity Microsoft Excel, PowerPoint, Microsoft Word, and Microsoft Outlook
5) Blockchain for Business
All of the company's courses are:
Pre-scripted, Hands-on, Laser-focused, Engaging, Real-life tested

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100 total reviews

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Amazing course that teaches from statistics to deepl learning. Very thorough. The instructors explain in a very easy way to understand even for the people that have no previous knowledge on the subjects. I loved it.I didn't give it 5 stars because, in some exercises, it lacks some further explanations on why they did some things and I believe they should also teach how to deploy a deep learning model. Apart from that, excellent!

It took a while to complete this course, but I think it was worth the effort. Very well framed and delivered course. Thanks a lot.

By Alejandro Guerrero on 2 months ago

Excellent course! It is very comprehensive and it really provides both a wide view of the field and great tools to work with. The videos make it easy to follow all the concepts and processes.

By Ivan Vrzogic on 4 months ago

Generally good as an introduction. However I would need to pass through the course at least once more, if not twice.

By S P on 4 months ago

This is an excellent, well presented course. If you are looking for a course that takes you from a total beginner to a data scientist, look no further.The one caveat all things, you will need to put in the effort, complete all tasks and do further reading/studying on your own. However, this course makes all of that easy, with a clear syllabus that includes stats, maths, programming as well as pointers on where to find additional information.

I recommend widely this course to people that have previous experience, mainly in statistics topics. It offers an excellent overview of all the necessary concepts, and this can reinforce our knowledge.In the machine learning topic, I was waiting for more complex exercises, these are very basic.

By Chris Signorelli on 2 months ago

The course overall has been a great match for me. There is a suitable balance between various levels of difficulty in the material. The only criticism is that perhaps the duplicate material between TensorFlow 1 and 2 lectures could have been omitted. Other than that minor point, the overall course was great as an introduction to data science. Much appreciated!

By Conor Galvin on 3 weeks ago

I learned a lot from this course. The course was really well laid out and really covered all bases from a beginner's level before getting to the more complicated stuff (after the 50% mark) like Machine Learning. This course is definitely accessible for anyone, although an aptitude for mathematics/programming would be ideal when trying to retain information. While I'm not sure how much of this course has stuck (as I didn't commit extra hours practicing every single aspect of it), I would be confident that if I ever ended up working with data in the future that there would be sections of this course that I could look back on that would be extremely valuable. The hardest part of the course was definitely trying to retain a solid understanding of the theory, while trying to wrap your head around all the different python libraries and then using the 2 in tandem. However, this would be overcome if you tackled the course at a slower pace and practiced. Overall though I would definitely recommend this course if you are any bit interested in Data Science and learning about its applications.

By Yerlan Mamesh on 2 weeks ago

The course basically covers everything one needs in studying data science. However, if you want to know more about the subject you should study additional resources for that.

By Saurabh Gairola on 2 months ago

The course is well-scripted, with relevant examples and discussions to guide new students through the data science journey. I am happy with the course but have some qualms too. To summarize:Pros-1. Well scripted, covering all relevant information required in a neat, orderly fashion.2. Tons of example and work exercises to help improve understanding.3. The use of real-life examples is a big bonus.Now the cons:1. So the only one and biggest con for me was the lack of information for Python. I felt lost most of the time with the python codes and had to read through various documentation to understand other relevant things (like the extra inputs that can be provided to a given function which is essential for future projects). This one is I guess more personal to me as I have no background in python (I use MATLAB) and I was hoping that the introduction to python and other examples would cover everything in depth. Also, the repeated errors in the given code (which the team has solved now) was a big problem, but that is expected due to the constant updates to python.Overall, it is one of the best courses that I have come across for beginners wanting to get an intuition about data science and an introduction to all the tools and theory, but not that necessary to master it.

By Andrew McAllister on a month ago

This was my first course here on Udemy and it was excellent! This course starts with the basics to make sure you understand the theory and concepts behind Data Science. It's a very comprehensive course, but is great for a beginner or if you are in need of a refresher. Would definitely recommend and will be checking out the other courses that 365 Careers Team has to offer!

By Ruth Kapanga on 4 weeks ago

It has been a comprehensive course and I have learnt a lot. I would love to go through it again and if there is another course related, i want to do it.Thank you!