Top 17 BEST Data Science & Analytics Certificates (2024)

Summary

This video script explores the top data science certificates that can launch a career in high-paying fields, even without prior experience or a degree. It reviews various beginner to intermediate level courses, including IBM and John Hopkins University offerings, emphasizing practical skills and theoretical knowledge. Certificates range from general data science and machine learning to specialized areas like data engineering and analysis, with some preparing for industry-recognized certifications. The script also highlights the importance of choosing the right course to avoid wasting time and to effectively enhance one's career prospects in the competitive job market.

Takeaways

• 📚 The script discusses the value of data science certificates for beginners and professionals looking to enhance their skills and career prospects in high-paying fields.
• 🎓 Certificates are a way to demonstrate completion of a course and can be added to resumes or LinkedIn profiles, potentially increasing job opportunities.
• 🛠️ The IBM Data Science Professional Certificate is designed for beginners and covers foundational tools, programming languages like Python, and a Capstone project.
• 🏫 The Data Science Specialization from Johns Hopkins University focuses on theory and uses the R programming language, delving deeper into statistical inference and regression models.
• 🌐 Microsoft's Azure Data Scientist Associate Professional Certificate prepares intermediate learners for a real certification exam and covers managing Azure resources for machine learning.
• 🔢 For those interested in the mathematical foundations of data science, there's a specialization in Mathematics for Machine Learning and Data Science, which covers linear algebra, calculus, and probability.
• 🤖 The Machine Learning Specialization by Stanford University is beginner-friendly and provides a solid foundation in machine learning concepts with a high satisfaction rating.
• 🧑‍💻 The Applied Data Science with Python Specialization from the University of Michigan is for intermediate learners, focusing on applying data science concepts using Python.
• 🔧 The IBM Data Engineer Certificate is a comprehensive program for beginners in data engineering, covering practical skills and knowledge with a mix of tools and technologies.
• 🌟 Duke University offers Python, Bash, and SQL Essentials for Data Engineering, aimed at beginners with a focus on these specific languages and their application in data engineering.
• 📈 For those looking to specialize in data analytics, the Google Advanced Data Analytics Certificate is a six-month program that covers a range of topics including Python, statistics, and machine learning.

Q & A

What is the main purpose of the discussed data science certificates?

The main purpose of the discussed data science certificates is to help individuals start a career in a high-paying field, learn high-paying skills, and get hired, even if they have no prior experience or degree.

Why might a quick course like the Google Data Analytics certificate not be sufficient for getting a job?

A quick course like the Google Data Analytics certificate might not be sufficient for getting a job because it is just one piece of the puzzle and does not provide comprehensive skills required for a data science role. It is more about combining courses to learn the right skills.

What are the key components of the IBM Data Science Professional Certificate?

The IBM Data Science Professional Certificate includes 10 different courses covering introduction to data science, tools and programming languages, methodology, Python, databases and SQL, data analysis visualization, and a Capstone project.

How does the Data Science Specialization from Johns Hopkins University differ from the IBM certificate?

The Data Science Specialization from Johns Hopkins University differs from the IBM certificate by focusing more on theory, using the R programming language, and delving deeper into statistical inference and regression models.

What is the advantage of taking the Microsoft Azure Data Scientist Associate Professional Certificate?

The advantage of taking the Microsoft Azure Data Scientist Associate Professional Certificate is that it prepares you for a real Microsoft certification, DP-100, which is a formal exam that can boost your credentials in the field.

Why is the Mathematics for Machine Learning and Data Science specialization considered important?

The Mathematics for Machine Learning and Data Science specialization is considered important because it covers underlying mathematical concepts that are fundamental to machine learning and data science, which can be beneficial for understanding and applying these concepts in practical scenarios.

What does the Machine Learning Specialization by Stanford University cover, and who is it suitable for?

The Machine Learning Specialization by Stanford University covers supervised machine learning, advanced learning algorithms, unsupervised learning, recommenders, and reinforcement learning. It is suitable for beginners who have basic high school math knowledge and are looking to master fundamental machine learning concepts.

How does the Applied Data Science with Python Specialization from the University of Michigan help in applying data science concepts?

The Applied Data Science with Python Specialization helps in applying data science concepts by focusing on real-world scenarios, including text mining, social network analysis, and using Python for data representation and machine learning.

What are the key areas covered in the IBM Data Engineer Certificate?

The IBM Data Engineer Certificate covers key areas such as NoSQL and big data, MongoDB, Cassandra, cloud computing, Apache Spark, SQL, ML, streaming, relational databases, ETL, and data pipelines.

How does the Google Data Engineering, Big Data, and Machine Learning on Google Cloud Platform specialization differ from other data engineering courses?

The Google Data Engineering, Big Data, and Machine Learning on Google Cloud Platform specialization differs by focusing on Google's own cloud services and is designed for those with some experience in data engineering looking to specialize in Google Cloud Platform.

What is the significance of the Microsoft Power BI Data Analyst Professional Certificate's focus on Power BI?

The significance of the Microsoft Power BI Data Analyst Professional Certificate's focus on Power BI is that it prepares individuals specifically for Microsoft's own data analyst certification (PL-300), which is industry-recognized and can be a valuable addition to one's resume.

Outlines

00:00

📚 Introduction to Top Data Science Certificates

This paragraph introduces the concept of data science certificates and their value in kick-starting a career in a high-paying field without prior experience or a degree. It emphasizes the importance of selecting the right courses to avoid wasting time. The speaker shares personal experience and relies on reviews and popularity to select the best Coursera certificates in data science, which will be discussed for their ability to teach high-paying skills and improve employability. The paragraph outlines the structure of the video, starting with data science and machine learning certificates, moving to data engineering, and ending with data analyst certificates, all aimed at beginners and judged on their utility and popularity.

05:02

🔍 In-Depth Analysis of Data Science Certificates

The paragraph delves into the specifics of various data science certificates, starting with the IBM data science professional certificate designed for beginners, covering a 5-month period with 10 hours a week of study. It includes 10 courses focusing on key data science tools and a capstone project. The discussion then moves to the data science specialization from Johns Hopkins University, which is slightly more theoretical and uses R programming language. The paragraph also covers the Microsoft data scientist associate professional certificate, which prepares learners for a real Microsoft certification exam, and the mathematics for machine learning and data science specialization, which is important for understanding the underlying concepts of these fields.

10:02

🛠️ Exploring Data Engineering Certificates

This section focuses on data engineering certificates, beginning with the IBM data engineer certificate, a comprehensive 5-month program for beginners covering practical skills and knowledge used by data engineers. It includes work with NoSQL, big data, and various data engineering tools, and ends with two capstone projects. The paragraph continues with the Google specialization in data engineering, big data, and machine learning on Google Cloud Platform, suitable for those with some experience looking to specialize in Google's cloud services. It also discusses the Microsoft Azure data engineering professional certificate, which prepares students for the Microsoft certified Azure data engineering associate certification.

15:02

📈 Data Analyst Certificates for Career Advancement

The paragraph introduces the top data analyst certificates, emphasizing their importance for beginners and those looking to transition into the field. It discusses the new Meta data analyst certificate, the Microsoft Power BI data analyst professional certificate, which includes exam preparation for the PL300 certification, and the Google advanced data analytics certificate, which, despite its name, is suitable for beginners with some experience. The paragraph highlights the importance of learning the right skills, such as Python and SQL, and the value of hands-on courses for building a portfolio.

20:03

📘 Comprehensive Overview of Data Analyst Certificates

This paragraph provides a detailed look at the IBM data analyst certificate, known for its practical approach and focus on Python, as well as the data Camp data analyst certification, which offers a quick and affordable way to boost one's resume. It also revisits the Google data analytics certificate, discussing its theoretical approach and the use of R instead of Python. The paragraph concludes by encouraging viewers to start with any course that suits their preference and use the knowledge gained to build a solid foundation in data analytics.

25:04

🌟 Wrapping Up the Data Science Certificate Guide

In conclusion, the paragraph reiterates the importance of choosing the right data science certificate based on personal preference, starting point, and learning objectives. It invites viewers to share their favorite courses and reasons in the comments, which could help others or inform future videos. The speaker also provides a link for viewers to try out the courses for free and wishes them good luck on their learning journey.

Keywords

💡Data Science Certificates

Data Science Certificates are educational programs that, upon completion, provide a credential attesting to the acquisition of specific skills in data science. In the video, these certificates are positioned as tools to help individuals, even those without prior experience or a degree, to start a career in a high-paying field. They are part of a bundle of courses that are professional certifications, which are mentioned as a way to enhance one's resume and LinkedIn profile.

💡Data Analytics Certificate

A Data Analytics Certificate is a type of professional certification that signifies the holder has completed a series of courses related to data analysis. The video discusses the Google Data Analytics Certificate as an example of a course that can help beginners get started in the field, emphasizing its comprehensive nature and the practical skills it aims to impart.

💡Machine Learning

Machine Learning is a subset of artificial intelligence that allows computers to learn and improve from experience without being explicitly programmed. In the context of the video, machine learning is a key component of several data science certificates, with the Machine Learning Specialization by Stanford University being highlighted as a course that provides foundational knowledge in this area.

💡Python

Python is a high-level programming language widely used in data science for its readability and efficiency in handling data. The video mentions Python as a main focus in several certificates, such as the IBM Data Science Professional Certificate, where it is used extensively throughout the course to teach data science concepts and tools.

💡R Programming Language

R is a programming language and software environment for statistical computing and graphics. The video contrasts the use of R in the Data Science Specialization from John Hopkins University with Python-focused courses, noting that R is especially popular in academia and research.

💡Data Engineering

Data Engineering refers to the practice of designing, building, and maintaining the systems and processes that enable the creation, storage, and use of data. The video script discusses various data engineering certificates, such as the IBM Data Engineer Certificate, which aim to teach practical skills and knowledge related to data infrastructure and big data technologies.

💡Capstone Project

A Capstone Project is a culminating academic task that demonstrates the skills and knowledge acquired throughout a course of study. In the video, Capstone projects are mentioned as a component of several certificates, allowing students to apply their learning in a practical context and build a portfolio for future job applications.

💡Professional Certificates

Professional Certificates are credentials that indicate a person has completed a course or series of courses in a specific field. The script explains that these certificates are like bundles of related courses, often aimed at beginners, and can be added to one's resume or LinkedIn profile to showcase their newly acquired skills.

💡Data Visualization

Data Visualization is the graphical representation of information and data, which makes it easier to understand and analyze. The video mentions data visualization as a skill taught in several certificates, such as the IBM Data Analyst Certificate, where students learn to create visual representations of data to facilitate better insights.

💡SQL

SQL (Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system. The script notes that SQL is an essential skill covered in many data science and data engineering certificates, as it is crucial for querying and managing databases.

💡Coursera

Coursera is an online learning platform that offers courses, professional certificates, and degrees from universities and institutions around the world. The video script frequently references Coursera as the provider of many of the data science and data engineering certificates discussed, indicating its role as a popular platform for professional development.

Highlights

The transcript discusses the top data science certificates that can help beginners start a career in high-paying fields without prior experience or a degree.

Certificates are a combination of courses that, upon completion, provide a document recognizing the learner's achievement, which can be added to a resume or LinkedIn profile.

The IBM Data Science Professional Certificate is recommended for aspiring data scientists, offering a 5-month program covering key tools and Python.

John Hopkins University's Data Science Specialization focuses on theory and uses the R programming language, suitable for those interested in academia or research.

Microsoft's Azure Data Scientist Associate Professional Certificate prepares learners for a real Microsoft certification exam, DP 100.

The Mathematics for Machine Learning and Data Science Specialization delves into the mathematical concepts underlying machine learning and data science.

Stanford University's Machine Learning Specialization is beginner-friendly and offers a solid foundation in machine learning concepts.

The Applied Data Science with Python Specialization from the University of Michigan is for those with some background knowledge, focusing on applying concepts to real-world scenarios.

IBM's Data Engineer Certificate is comprehensive, covering practical skills and knowledge used by data engineers in their daily roles.

Google's Data Engineering, Big Data, and Machine Learning on Google Cloud Platform specialization is ideal for those with some data engineering experience looking to focus on Google Cloud.

Microsoft Azure Data Engineering Professional Certificate prepares learners for the Microsoft Certified Data Engineering Associate certification, DP 203.

Duke University offers a course on Python, Bash, and SQL Essentials for data engineering, suitable for beginners with no programming or data engineering knowledge.

DataCamp provides a Data Analyst Certification with a unique testing approach, including both timed and practical tests.

Google's Advanced Data Analytics Certificate, while labeled as advanced, is suitable for beginners with foundational knowledge and focuses on Python.

The IBM Data Analyst Certificate is highly rated and covers a range of topics from Excel to Python, aiming to kickstart careers in data analysis.

The Google Data Analytics Certificate is a classic choice for beginners, focusing on theory and practical application, though it has received criticism for its lack of practicality.

Choosing a course depends on personal preference, starting point, and learning objectives; the transcript encourages starting with any course to begin the learning journey.

Transcripts

the 17 best data science certificates

they can help you start a career in a

high-paying field and get closer to a

job even if you have no prior experience

or no degree but let's be realistic if

you're starting from zero a quick course

like the Google data analytics

certificate is not going to get you a

job instead it is about combining these

to learn the right skills but not all

certificates and courses are the same

and if you take the wrong ones you'll

risk wasting lots of time even months

with nothing to gain so today I want to

cover the best corsera certificates for

data science that can help you learn

high paying skills and actually get

hired if you're wondering how I select

these courses I'm using personal

experience with some of these as well as

what I hear from other people but more

importantly the reviews they're getting

and their popularity so I'm putting all

of this research together to show you

the best data science certificates first

let me quickly explain what certificates

are you take courses and after

completion you'll receive a final

certificate and it's basically just a

piece of paper stating that you've done

something and you can add this to your

LinkedIn or your resume or print it out

and I love collecting these it kind of

becomes like an addiction nowadays we

call a bundle of courses professional

certificates and it's like a few courses

related to a specific career often for

beginners bundled together in a package

in this video certificates refer to

courses that give you a certificate once

you finish it now I think we're on the

same page so let's get started the first

one is going to be the data science and

machine learning certificates and then

we'll dig into the data engineering ones

and finally talk about the data analyst

certificates all of these will be for

complete beginners and all of these will

also be very useful so make sure you

stick around until the end because if

you use these correctly and you get the

right ones they can actually help you

improve your career significantly and I

mean these are some of the highest

paying jobs available out there right

now first up on the list we have the IBM

data science professional certificate

this one is for aspiring data scientists

and in general those who are looking to

break into Data dat science whatever

your job you're looking for it's

beginner level 5 months at 10 hours a

week and you learn some of the key tools

data scientists need to get the final

certificate you have to complete 10

different courses and this includes

basic introduction to data science a

course about the tools and programming

languages a course about some of the

methodology and you'll also do a python

project and Learn Python in general

while also learning about databases and

SQL and in course number seven you'll

also do a little bit of data analysis

visualization and finally machine

learning and everything in this one or

pretty much all of it is using python so

it's a lot of python in this course you

will also do a Capstone project which is

kind of like a final project that you

can put in your portfolio later so how

can this one help you if you're looking

to move into data science well python is

definitely a skill to learn it's very

valuable and in this course you're

focusing on python as the kind of main

thing so it's definitely one of the big

advantages this is going to give you a

strong foundation for whatever you want

to do next although it is a a pretty

short course so it's definitely not

enough to become a data scientist but

rather I see it as a piece in the bigger

puzzle so let's continue number two on

the list is the data science

specialization from John Hopkins

University it's also for entry-level

people looking to become a data

scientist now this one is a little bit

different and it's actually from a

university and not from a company John

Hopkins is a major us-based university

with a strong reputation universities

tend to focus more on Theory rather than

practical stuff so we'll see what this

course actually looks like it's also

beginner level and 7 months at 10 hours

a week so a little bit longer than the

IBM one there are 10 different courses

in the program and they're relatively

similar but you'll find a lot of

differences to the ibm1 as well in the

beginning they give you an introduction

to what a data scientist does and then

you'll start working with r the r

programming language is going to be a

key part of this course and you'll also

use it for most of the other courses the

major difference here is that it

actually digs deep deeper into things

like statistical inference and

regression models when it comes to the

Practical side it is only 8 hours or

technically another course developing

data products as well as a capson

project but the main difference here is

that this one is focusing on R and the

other one is working with python

exclusively whether you should pick r or

python is completely up to you and we're

going to go through courses that include

both of them python is more in demand

and there are more job openings in

general but R is also very popular

especially in Academia or research so it

does make sense that the university

focuses on this language next up on the

list we have a Microsoft certificate and

these ones are very popular and for good

reason it's the Asia data scientist

associate professional certificate now

this one is for an intermediate level

but I actually check the specific

recommended experience and it's really

not that much if you've taken a course

like the two we mentioned before or you

know either of them then you should be

just fine here you'll learn how to

manage Asia resources for machine

learning deploying operationalized

ethical machine learning Solutions as

well as run experiments and train models

there are only five different courses in

the certificate and the final course is

actually preparing for DP 100 DP 100 is

a real certification so a specific exam

that you take directly from Microsoft

it's completely optional and you don't

have to take it and you'll still get

your professional certificate but if you

do want to take that option it can be a

great thing to do as well I would say

that it's probably the main advantage

about this one is that it directly

prepares you for a real Microsoft

certification if you're wondering what

the difference is between a certificate

and a certification well the definitions

can be a bit blurry but in this instance

I'm referring to certificates as the

course completion certificates and

certifications as the things you get

when you take a formal exam you know

with a proctor in a more real formal

setting all right next up on the list is

more specific but also very important I

think it's something that most people

are missing especially in data science

employers are probably going to respect

you a little bit more especially if you

don't have a technical background and

it's the mathematics for machine

learning and data science specialization

now this one digs deep into some of the

underlying mathematical Concepts that

make machine learning and data science

function that it's based on so it is a

very good idea to dig into some of these

as soon as possible if you already have

a degree in a quantitative field you've

probably already worked with some of

these Concepts such as statistics and

linear algebra but now you can actually

brush up on them and apply them to real

data science scenarios now this one is

also beginner level and 3 months at 5

hours a week there are only three

courses but they are pretty long so just

be aware of that and the first one is

linear algebra for machine learning and

data science the second course is called

calculus and the third one is about

probability and statistics now in these

30 hours give or take per course you

don't really have time to learn

everything about these topics they're

very very big topics and there is a lot

to learn and this one is definitely not

not supposed to replace these three math

courses at University or college but

it's more a way to boost your knowledge

and get introduced to them if you

haven't heard about it before it's also

going to help you apply these Concepts

in a more practical scenario or

practical setting so it's perfect for

those who are interested in data science

especially those who feel afraid of the

math and you don't have to be afraid

just take this course now if you want to

focus on machine learning itself there

is a better course for it and it's the

machine learning specialization by

Stanford University it is also beginner

level but but it recommends basic high

school math and the rest is kind of

explained in the course I would say that

if you're taking the math course that I

just mentioned you should definitely

take this before the machine learning

course because it's going to give you a

really solid foundation to help

understand some of these Concepts and

make this course way easier for you but

if you don't want to do that that's

completely fine it's still made for

beginners but I want to emphasize that

it's not meant to be easy by any means

it is machine learning after all now in

this one there are three different

courses the the first one is supervised

machine learning the second one is

Advanced learning algorithms and the

final one is unsupervised learning

recommenders and reinforcement learning

I would say that it's probably one of

the best ways to dip your toes into

machine learning and master the

fundamental concepts Professor Andrew is

also famous for his quality teaching and

I do think that it's a very good use of

your time it's only 2 months to 10 hours

a week and while the concepts are

supposed to be hard the 4.9 rating from

20 2,000 reviews shows that people are

very happy with this one and I rarely

see a rating that's as high as this

course next up is applied data science

with python specialization from

University of Michigan it is 4 months at

10 hours a week and intermediate level

now here's where we again need to Define

intermediate level in this case it's an

applied data science course and that

means that they focus more on applying

the concepts to real world scenarios or

at least doing something with the

concepts to do that you'll need to have

some of the the theoretical and

background knowledge as well now in the

first course you're being introduced to

data science in Python but it's not

really an introduction to data science

itself and that is why I think you

should have taken at least one program

where you actually learn the basics of

data science before you take this one

but that's pretty much all you need now

there are five different courses in this

one and the first one is just the

introduction then it focuses on applied

plotting sharding and data

representation in Python and then it

applies machine learning text Mining and

social network analysis so who should

take this course I think it's pretty

straightforward and it's for people who

have learned the basics but want to

focus on Python and also start applying

what they've learned if you're feeling

stuck and you've learned the theory and

you want to get to doing stuff this is a

perfect course for you it's been highly

rated so I do think that you should

definitely give it a try moving on to

the data engineering certificates and

then we'll get to the data analysis once

in a second we've still got 11 amazing

certificates left so we're only just

getting started and these ones can teach

you some of the best high income skills

and help you get a job that you're

looking for the first one on the list is

the IBM data engineer certificate this

one is really exciting because it's a

mix of different programs and it's very

comprehensive but still it's only 5

months at 10 hours a week and it's

beginner level so it's pretty easy to

complete this one you'll actually focus

on the practical skills and knowledge of

data engineers and what they use in

their daily roles you'll work with nosql

and big data using mongod DB Cassandra

cloudin had dupe Apache spark SQL ML and

streaming it also teaches you relational

databases creating designing and

managing them and don't forget ETL and

data pipelines you'll also learn all

about that stuff extract transform load

and classic data engineering tasks I'm

not going to go through every course but

as you notice some of these are actually

in other IBM certificates such as the

IBM data science certificate and that is

also why you'll see some courses with

30,000 ratings and some courses that

barely have 200 it's that they're part

of other programs as well so they take

the ratings from those programs now I

think this one is a pretty comprehensive

course and if we do look at the reviews

there are 4,200 reviews for the 4.6

rating and two of these 13 courses are

also practical projects with one python

project and one final Capstone project

so you should at least have two projects

in your portfolio when you complete this

one building a portfolio early is

definitely going to help you on the job

market and I don't really have anything

negative to say about this one I do

think that it's going to teach you a lot

of the core data engineering skills but

is it going to help you get a job in

data engineering right away I would say

no it's still quite a short course and

most people that get into the field

either have some experience or degree

and if you don't then continue learning

or get to another data role and then you

can progress from there and eventually

reach your goals next we have a Google

specialization and it's data engineering

big data and machine learning on Google

Cloud platform now gcp is a cloud

computing platform similar to AWS and

Microsoft Asia and in this one you'll

focus on data data engineering but do it

specifically with Google's own cloud so

this one is for you with some experience

in data engineering and you're

specifically looking to focus on Google

Cloud platform you don't need to be an

expert but you do need some basic

understanding of the concepts that

you're going to be working with in this

course it's pretty short at only one

month at 10 hours a week so it's

basically 40 hours and there are five

different courses the first one teaches

you big data and machine learning on

Google Cloud the next one focuses on

data lakes and data warehouses and then

building data badge pipelines and then

resilient streaming analytics systems on

Google cloud and finally it's smart

analytics machine learning and

artificial intelligence so again who

should take this course I think it's

somebody who's looking to specialize in

this platform with some experience of

data engineering you don't need to be an

expert but if you're looking to learn

the fundamentals from scratch I don't

think that it's the right course the

next one is even better though and I'll

explain why it's the Microsoft Azure

data engineering professional

certificate this one is also

intermediate level and you should have

some understanding of data engineering

and tools SL programming languages like

SQL python or Scala it is 3 months to 10

hours a week so it's pretty short as

well there are 10 different courses in

this one all of which focus on data

engineering tasks and Microsoft aure the

interesting thing here is the final

course which is called prepare for DP

203 now DP 203 is also known as

Microsoft certified Asia data

engineering associate it's a real

certification that you can take on

Microsoft's website where you basically

take a formal exam viewed by a proctor

and then you pass and you become

certified by Microsoft and the thing is

that this entire program is preparing

you for this certification so while it's

giving you a professional certificate

that teaches you everything it is also

giving you the option to prepare for a

real certification if you want to take

it and that is probably the main benefit

if you're already taking a course then

why not take a course that specifically

prepares you for an industry recognized

certification now of course make sure

that you look into this one and see that

it's something for you I talk more about

the certification in my data engineering

video and I'll show you how to find this

video at the end of this video because

I've still got a lot of great

certificates left to show you number

four on the list is from Duke University

and this one is one of the most

prestigious schools in the US and now

you can take a course from them and get

certified this one is called python bash

and SQL Essentials for data engineering

and it's 4 months at 5 hours a week so

the estimated workload is around 80

hours they don't require any programming

or data engineering knowledge but you're

going to learn a lot in the program so

it's supposed to be for beginners they

do recommend that you understand the

basics of Linux but honestly it's fine

as long as you understand what it is and

there's a whole course about it in the

program now there are four different

courses the first one will teach you

Python and specifically the Panda's

library and how to apply to data

engineering there's also a course about

Linux as I said and Bash as well as

scripting with python and SQL and

finally web applications and command

line tools for data engineering the main

benefit here is that if you're looking

to Learn Python bash and SQL this is a

fantastic opportunity to do so while

applying it to data engineering one

major mistake that people make when they

learn a programming language is that

they learn it for a general use case but

for example when it comes to python

there's so much that you can learn you

can use Python to literally build

anything it's super versatile so if you

focus on the data engineering aspect

then you should specifically Learn

Python for data engineering

specialization is really the key to

success and you don't have time to learn

everything about python so I really

appreciate that there are courses that

actually specialize and focus on the

skills that you want to learn now the

next course on the list is also from

duke and it's pretty similar and it's

called applied python data engineering

specialization I do have some pros and

cons so wait a moment now this one

requires a stronger mathematical

foundation and programming knowledge

it's 5 months to 10 hours a week and

it's slightly longer than the other one

but this one actually focuses on

elevating your coding skills with data

engineering and using big data for

decision making analysis Ai and machine

learning there are only three courses in

the program and it's not as popular and

it's also pretty new but I think it's an

untapped gem the first course is

focusing on spark Hadoop and Snowflake

and learning these tools the next one is

virtualization Docker and kubernets and

finally data visualization with python

so who is this course for well I would

say certainly not complete beginners

since you have other things to spend

your time on like the fundamentals but

it's more for somebody with some

experience that want to focus on these

things I'm also slightly suspicious

about their views and it's only received

3.7 and 3.5 and that's not terrible but

for these courses it's not the best

either I think it's because people

enroll in this one thinking that it's

going to be easier than it actually is

but it does require significant

experience especially on the

mathematical side and when it comes to

the actual curriculum I do think that it

looks very good so if you are the right

fit then you can definitely give it a

try now it's time to get into the data

analyst certificates and these ones are

probably the best for beginners when I

get into the Fe field and get a data

analyst job you can also use them to

transition and get other jobs in the

field and I want to show you the best

data analytic certificates available on

the market and I will also compare these

certificates with each other as we go

along data analyst jobs are amazing but

the honest truth is that the job market

is very competitive especially for

beginners so it really is important that

you take the right courses get the right

certificates and focus on the right

skills that employers actually look for

as we've seen many of these courses take

a lot of time so you really don't want

to waste time on the wrong course and

I've heard from so many people that

regret the course that they spent their

time on and wish that they could just go

back and start over and do things

differently so let's get started with

the top six data analyst certificates

the first one on the list is the new

metadata analyst certificates it is for

complete beginners 5 months at 10 hours

a week and as I'm recording this the

final course is not even available but

when you're watching this it's probably

not going to be a problem there are five

different courses and the first one is

an introduction to data analytics and

then it moves over to spreadsheets and

SQL and then a little bit about Python

and course 4 is about statistics and

finally course five is about data

management this one is supposed to be

metas equivalent to the IBM and Google

data analytic certificates but we still

have a lot to cover so will so we'll

compare them more later next up we have

the Microsoft powerbi data analyst

professional certificates this is a very

interesting one and it's a great option

but not for everybody

now it's a beginner level sech 5 months

at 10 hours a week so it's just as long

as the previous one it is also pretty

new but has an insane amount of

enrollments for being so new and it's

really popular and there are fantastic

reviews which is not surprising

considering how it's from Microsoft

there are eight different courses in

this certificate and the first one

covers data preparation using Excel and

then harnessing the power of data with

powerbi so basic data analytics with

powerbi and then we have ETF with

powerbi there's also data modeling data

analysis and visualization and creative

designing in powerbi and this basically

means creating reports dashboards and

different visualizations and finally we

have deploy and maintain assets as well

as a Capstone project for those

wondering a Capstone project is

basically a final project that you do

under their guidance and it's a very

good way to start building your

portfolio with some projects in this

certificate there is also a final course

which focuses entirely on exam

preparation and practice it is supposed

to help you prepare for the pl300 exam

which is Microsoft's own data analyst in

powerbi certification I know that it can

get messy with certificates and

certifications but pl300 is basically a

formal exam that you take either online

or at home and once you pass you're

officially a Microsoft certified data

analyst this is one of the main benefits

of this professional certificate and

it's a normal course but it will also

help you prepare for one of Microsoft's

certific if ation pl300 is industry

recognized and will look very good on

your resume and as a bonus you actually

get 50% off the pl300 exam fee once you

complete this certificate on corsera I

still want to mention the downsides to

this course because I think it's

important to consider all of the sides

and here the only bad thing is that it

only focuses on powerbi so if you're

looking to learn things like SQL and

python which you should then you're

going to have to learn them on the side

or using one of the other courses that

will cover up next number three is a

perfect course for those looking to

focus more on python it is the Google

advanced data analytics certificate it

is 6 months at 10 hours a week and they

claim that it's advanced level but if we

actually look at the details it does

require prior knowledge of foundational

analytical principles and tools so it's

definitely not advanced level but I

think you could take this one starting

from zero if you want to but ideally you

would have some experience and it's

probably a better idea to take one of

the other courses first to give you that

foundational knowledge to make the most

out of this course it focuses on

teaching you skills like statistical

analysis python regression models and

machine learning in less than 6 months

although most people complet it way

faster looking at the curriculum you

will see seven different courses the

first one is kind of an introduction to

data science and then an introduction to

Python and then of course about data

analytics and translating data into

insights which is what they're actually

claiming the course is about but as you

can tell it's a lot of Mach machine

learning and data science things as well

the next course is about statistics

which is very interesting many courses

will skip statistics but they actually

give you this foundational knowledge and

I think it's going to be very helpful

and make you stand out there is also a

long course on regression analysis and

of course machine learning as well and

then they finish off with the Capstone

project so how can this course help you

and who is it really for I wouldn't say

that it's really a data analytics

certificate and I mean sure many things

are going to be useful and many things

are related but when it comes to the

machine learning course for example it's

not relevant for entry-level data

analysts at all so if you're limited on

time then you don't want to take all of

these courses but if you're looking to

move more towards data science later

this could be a really good way to

become a more technical data analyst and

explore those areas as well while

learning data analytics in the first

place so you can also see if this is

something for you I also want to give a

big shout out that they do teach python

in many of the courses which is very

very good but unfortunately not SQL so

make sure that you learn SQL on the side

as well number four on the list is also

very exciting and it is the IBM data

analy certificate it's very popular but

is it still worth it now it's for

complete beginners and you'll have to

spend four months working 10 hours a

week and it also has a 4.7 rating out of

five from nearly 20,000 reviews which is

absolutely amazing there are nine

courses in the certificate and the goal

is to help you begin your career as a

data analyst so in the first course it's

basically just introduction to the field

and then you move into Excel in the

second course and then start working

with data visualizations and creating

dashboards and both using Excel and

cognos and if you don't know what cognos

is it's basically IBM's version of

powerbi or Tableau you could say there's

also a python course as well as a python

project and then you'll have to learn a

little bit on databases and SQL and

combine that with python as well and as

you might have noticed there's also a

lot of python in this course which I

think is a plus especially because it's

so useful and many EMP are looking for

python skills the next course is data

analysis and then data visualization and

then finish up with a Capstone project

and all of this with python as well and

then you're done so how can this one

help you well I would say that it's a

great one if you're looking to learn the

basics and focus on python it's known to

be more Hands-On and more practical than

Google's version at least referring to

the original certificate maybe not the

advanced certificate but I would also

say that it's slightly less polished

than the Google version the videos are

not as nice but they're focusing more on

the concept cepts they're basically just

slide presentations and very basic but

in my opinion it really gets the job

done and IBM's course has really good

reviews and it's been around a long time

even before Google so there's definitely

a lot of good things to learn from this

one number five is the data Camp data

analyst certification now data Camp is a

platform offering trainings and courses

for data science and this one is

different and it's not on corsera but I

wanted to includeed as a bonus because

it's very popular for good reason

instead of taking a course you can take

the ex whenever you're ready and you

basically just join data camp and you

get access to all of their courses and

all of their resources all at once when

you're ready to sign up for the

examination it's actually two tests one

is time based and you have to answer

questions that test your knowledge with

a time limit and the second part is a

practical test where you'll be tested on

your ability to implement a working

solution for a data problem you're

basically doing some common data analy

tasks and then you'll be tested on your

ability to do so and for this one you

can always choose if you want to focus

on python or R and take the test using

one of these languages you don't have to

take it in both but SQL is always going

to be included now the main advantage of

data Camp is that it's actually very

affordable and a quick way to boost your

resume especially if you've taken

courses in the past you can literally

just sign up take the test and be done

or use the resources to study if you

need to but now let's move on to the

final certificate and I'm going to

compare this one to the other options as

well and I'm of course talking about the

Google data analytics certificates this

is the classic one that everyone's heard

of and it's it's brought so many people

into the field of data analytics but is

it actually the best option it's really

a personal preference I do like it a lot

but there are some people that just

don't like it and I understand why as

well it's not the most practical course

and it's 6 months at 10 hours a week so

it's pretty long even if it is for

beginners if you do look at the courses

there are eight different ones and many

of these don't use python or something

and focus on a specific tool it's more

doing a lot of things in Excel or just

listening to presentations and

understanding the theory and for being

so unpractical it does get a lot of hate

but I would say that if you go in it

with the right mindset it can be a very

useful course it helps you get into

thinking like a data analyst and it

takes it very slowly sure it's not going

to prepare you for jobs right away nor

are you going to know exactly how to do

everything but if you do start with this

one and then you apply your skills in a

more practical course you'll have a

really solid understanding both of the

theory and the actual practical aspect

as well when it comes to the specific

skills it's also teaching you R and not

Python and that can be a downside

depending on your preference but you

also get to try R and it's pretty cool

as well picking a course is a lot about

personal preference as well as where

you're starting from and what you want

to learn and I want to hear your opinion

in the comments share which one is your

favorite and why and your opinion might

help somebody else or help me make

another video in the future I've shown

you many Great Courses but the most

important thing is just to get started

and if you're confused just pick one and

give it a try and I'll leave a link in

the description where you can try them

out for free thanks than for watching

and good luck on your journey