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Become a Data Scientist

Data Science Bootcamp

Online

Campus

20-24 Weeks

Course Duration

25h/Week

Time Commitment

4.8 Star

Rating on Course Report

+$26,500

Average salary increase

Metana students who provided pre- and post-course salaries.

$145,242

Data scientist’s average salary

Source: Glassdoor

Why Metana?

Metana Students get hired

1-on-1 mentorship, coaching and career services

Find the answers you can’t Google

Industry-Experienced Instructors

In-Demand Curriculum

AI for Engineers learning unit + AI interactive learning series

Plus, our online Data Science Bootcamp covers all relevant languages, tools, including:

Overview

Metana is one of the longest-running and most successful Web3 bootcamps on the internet. Metana’s graduates are equipped to succeed in the professional world through Metana’s foundational teaching method & its JobCamp™️ allows students to thrive in their first job and every job after.

Data science is the driving force behind the future of AI, revolutionizing industries and transforming the way we solve complex problems. If you’re a software developer eager to dive into the world of machine learning, the AI/ML bootcamp’s 20-week machine learning phase is your passport to a thriving career in this dynamic field.

This comprehensive course combines advanced machine learning concepts with a focus on deep learning, classical algorithms, and their applications in business. You will gain a deep understanding of the mathematical foundations behind machine learning, explore state-of-the-art techniques, and learn how to leverage machine learning in business settings.

AI ML market value of nearly $100 billion 💰 is expected to witness explosive growth and reach almost $2 trillion by 2030

CAGR of 32.9%🔥🔥

Source: Statista

Curriculum

Week Content
1. Introduction to Advanced Machine Learning Review of machine learning fundamentals Mathematical foundations in machine learning Overview of deep learning, classical algorithms and business applications.
2. Linear Algebra for Machine Learning Vector spaces, matrices and operations eigenvectors and eigenvalues Singular Value Decomposition (SVD) and it’s applications Principal Component Analysis (PCA)
3. Data Transformation and Integration Partial Derivatives and gradients Optimization techniques (Gradient descent, stochastic gradient descent)
4. Data Reduction Techniques Probability distributions: discrete and continuous Statistical inference and hypothesis testing Bayesian inference and probabilistic modelling. Expectation-maximization (EM) algorithm.
5. Feedforward Neural Networks Deep learning architectures (Perceptron, feedforward neural networks) Activation functions and network intialisation Backpropagation algorithm and training neural networks Optimization techniques for deep learning neural networks (Adam , RMSProp etc.)
6. Convolutional Neural Networks (CNN) Introduction to CNNs for image analysis Convolution and pooling layers Object detection and image segmentation Transfer learning with pre-trained CNNs
7. Recurrent Neural Networks (RNNs) and Sequence Modelling RNN fundamentals ( Architecture, Hidden states and Memory cells) Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRUs) Sequence generation and language modelling Applications of RNNs ( Text generation, Machine translation, Speech recognition)
8. Generative Models and Unsupervised Learning Generative Adversarial Networks (GANs) Variational Auto encoders (VAEs) Clustering algorithms: k-means, Hierarchical clustering Dimensionality reduction techniques (t-SNE, UMAP)
9.  Classical Machine Learning Algorithms Decision trees and ensemble methods (Random forests, Gradient Boosting) Support Vector Machines (SVMs) and kernel methods Naive Bayes and Gaussian Mixture Models (GMMs) Instance-based learning including k-Nearest Neighbors (K-NN)
10. Machine Learning in Business Introduction to machine learning in business applications Predictive modelling and customer segmentation Recommender systems and personalization Time series forecasting and anomaly detection
11. Reinforcement Learning Markov Decision Processes (MDPs) Q-learning and Deep Q-learning Policy Gradient methods Model-based reinforcement learning
12. Advanced Topics in Machine Learning Transfer Learning and domain adaptation Explainability in machine learning models Adversarial attacks and defences in deep learning Fairness, bias, and ethical considerations in machine learning Fairness, bias and ethical considerations in machine learning
13. Machine Learning Deployment and Scalability Introduction to deploying machine learning models in production Model serving and APIs Scalability and distributed machine learning Monitoring and performance optimization
14. Ethics and Responsible AI Ethical considerations in machine learning Bias, fairness and transparency Privacy and data protection Regulatory frameworks and guidelines
15. Project work and Case studies Undertake a machine learning project or work on business case study Apply the concepts and techniques learned throughout the course Gains hands-on experience with real-world datasets and business scenarios

**Note: This course outline provides an overview of the topics and structure. The actual course content may be adjusted based on the pace of learning, the specific interests of the participants, and recent advancements in the field.

According to a study published by McKinsey Global Institute, the U.S. economy could be short as many as 250,000 data scientists by 2027.

Meet the Instructor

Imesh Ekanayake

Imesh has been in the AI/ML space since early 2015 and is currently working as a Consulting Analyst- McKinsey & Company.

Imesh has been an Instructor since 2020 at University of Peradeniya which is one of the prestigious universities in Sri Lanka.

Tuition

We offer three options to get your career change started. All plans include a full refund policy if you do not get a job after graduating.

This investment includes a full year of access to our data science course material. Additionally, the course offers live events, AMA sessions, personalized support from the instructor, and a certificate of completion for those who complete the course.

You can pay your tuition via card, bank transfer, or crypto.

  • Non-Job-guarantee discount – $1,000 (If you choose to not have the job guarantee, you get an additional discount)

Pay Upfront

$9,450  $7,990

Pay upfront & save up to 32% on tuition for a limited amount of time.

  With Job-guarantee Without Job-guarantee
Total tuition before discount $9,450 $9,450
Discount - $1,460 - $1,460
Non-job-guarantee Discount   - $1,000
Paid at enrollment $7,990 $6,990
Total tuition $7,990 $6,990

Month-to-month

$9,450  $1,460/mo

Pay monthly. Save up to 28%

  With Job-guarantee Without Job-guarantee
Total tuition before discount $9,450 $9,450
Discount - $1,110 - $1,110
Non-job-guarantee Discount   - $1,000
Paid at enrollment $2,500 $2,500
Monthly payments during course (4) $1,460 $1,210
Estimated total tuition $8,340 $7,340

Personal loan

$69-$214* /mo

Apply for a loan & pay it off in installments.

Some students use personal loans to pay for their education. There are many personal lending options for you to research and consider.

Keep in mind that Metana does not endorse, recommend, or promote any particular lender. The payment choice is at the discretion of you, the student. If you decide to use a personal loan, make sure to choose the option that works best for you.

Below are a few options; personal loans may also be available through your personal financial institution.

Apply for Meritize loan

 

*You can borrow less, but need to pay the tuition difference upfront. Only available for U.S. citizens/permanent residents.

**Tuition will increase to $12,980 for all cohorts in Dec 2023. To lock in the current tuition rate, pay your tuition in full or the first month’s installment and enroll in a cohort that begins in 2023/24. You’re eligible for a 100% refund till 2 weeks after starting the cohort. 🌱

Roles and Salaries

In the field of data analytics, there are diverse career paths that individuals can pursue based on their skills and experience. Data analytics involves extracting insights from data to drive informed decision-making and solve business problems. If you’re interested in a career in data analytics, there are several roles you can consider, such as Data Analyst, Data Scientist, Business Intelligence Analyst, and Data Engineer.

PositionAvg Yearly SalaryMin Yearly Salary
Max Yearly Salary
Data Scientist (Associate)$112k$89k$145k
Data Scientist$126k$103k$165k
Machine Learning Engineer(Associate)$128k$100k$166k
Machine Learning Engineer$133k$105k$171k
Data Engineer$116k$92k$148k

Please note that these salary ranges are approximate and can vary based on factors such as location, industry, company size, and level of experience. It’s always recommended to research specific job listings and consult reliable salary data sources for the most accurate and up-to-date information.

According to Indeed, the average salary for a data scientist in the United States is over $128,000 per year. This high salary results from the demand for data scientists and the value they bring to organizations.

Upcoming Cohorts

We have monthly cohorts. You can always choose to pause the program and resume where you left off if it’s too fast-paced for you or if life gets in the way. There is no financial cost associated with this. We want you to succeed and won’t make you follow a schedule that doesn’t suit you.

Admission Policy and Process

You have to prove your seriousness in learning and then only you are admitted to our bootcamp. This makes our admission policy as unique as our Bootcamp.

Admission Policy

  • 6 months of active coding experience with a general-purpose programming language (e.g., Python, R, Java, C++).

  • Comfort with basic probability and descriptive statistics, including concepts like mean and median, standard deviation, distributions, and histograms

  • You must be proficient in English.

  • The coding test result you receive will be the most important component of your application.
Most Comprehensive Data Analytics Career track

Don’t meet the requirements? Our Data Analytics bootcamp might be an ideal place to start.

Start your data science career with our data analytics bootcamp! Gain hands-on experience with real-world data assignments and expert guidance from experienced instructors. Don't miss out on this opportunity to launch your career in this rapidly growing industry.

Admission Process

Submit your application

Start your new career by completing our short application.

Complete the coding test

Gauges readiness for the fast-paced, intense immersive program.

The Interview call

Schedule an interview call with one of our student admissions officers

  • After you submit your application & schedule an interview call with one of our student admissions officers, You will receive an email with a link to a coding test. (dates are available within 3-7 days from the application date)
  • You need to complete the coding test within 3 days.
  • Send us an email if you need more time ([email protected])
  • Your application will be rejected if your score falls short of a predetermined level. Because we need to compare your application to those of the other applicants for the upcoming cohorts, we can’t always make a decision right away.
  • We limit cohorts to 10 students per month to ensure maximally effective learning outcomes. If you have a great application but didn’t quite make it in, we will offer to waitlist you for the upcoming month.

Career Success - Metana's JobCamp™️

Our career success team gives our students the professional skills they need for their first job and every job after. Knowing how to get a job is critical, which is why our Career Success team helps you graduate ready for the job search. And even after you graduate, our team is available to keep you motivated, prepare you for interviews, and even help you negotiate offers.
First Impressions
Make a brilliant first impression. LinkedIn, GitHub and Resume templates and guidance.
The Hunt
Learn to build connections, how to look for jobs, and explore starting as a freelance.
The Interview Process
Learn about both the technical and non-technical parts of an interview. How to prepare effectively.
Technical Know-How
Learn common data structures and algorithms, and describe them during a whiteboard interview. Practice coding techniques for take home assignments.

Our students work at

Frequently Asked Questions

15% Tutorials, 85% Coding. Group office hours will be held once a week & with a weekly one-on-one session

All content will be delivered through video & text using our LMS. 

Each week at Metana includes four key events:

  1. A group class and discussion lasting for 1 hour. Students are encouraged to prepare a list of questions for the instructor ahead of time, and the next week's assignment will be introduced and clarified during this meeting. The group class also provides an opportunity to discuss recent crypto events and explore more in-depth blockchain concepts that may not be covered in the curriculum.
  2. A 30-minute one-on-one code review session with an instructor, during which the instructor will provide feedback on the code written during the previous week.
  3. Time dedicated to studying materials for that week's topic. Materials may include reading or video resources provided by Metana.
  4. Completing the new assignment, which will typically take up the majority of the week.

In addition, Metana also provides support for interview preparation and instructors are available to work closely with students to get them ready for pending interviews.

Personalized Instruction. Every week you will spend half an hour one-on-one with a senior engineer who will do an expert review of the code you wrote for the assignments. He or she will point out mistakes and suggest improvements. If serious mistakes are found, you must go back and fix them. (If you don’t like taking direct feedback on how to improve, Metana is not for you!)

Small Cohorts. In addition to your weekly personalized meeting, you will meet 1 hour per week with your cohort and the instructor to discuss what you learned, ask hard questions, discuss crypto news, and generally have an awesome discussion with smart and passionate people. Each cohort has a hard cap of 10, and we frequently make it smaller. You will be surrounded by like-minded people who help keep you accountable and stay on track.

Hands-on Emphasis. There is no tutorial hell with Metana. At least 80% of your learning hours will be spent coding or hacking.

Extremely Rigorous Curriculum. Although 80% is practice, the remaining 20% of theory matters too. We don’t see theory and practice as either or. We want you to know the fundamentals and the minute details of how things work.

We go way beyond other courses in what we require you to understand.

For example, towards the end of the course, you will be writing non-trivial smart contracts completely in assembly (Yul), breaking incorrectly used public signature cryptography, creating an Ethereum wallet from scratch, using testing techniques most developers have not heard of, reverse engineering the compiler output without the aid of a decompiler, and recreating hacks that have drained applications of millions of dollars.

You will understand at a deep level how smart contracts store various kinds of data on the blockchain and how transactions are formed and interpreted.

Familiarity with Python is crucial for our data analytics bootcamp. Python's versatility, ease of use, and extensive ecosystem of data analytics libraries make it an ideal choice for data manipulation, analysis, and visualization.

It's recommended that you are familiar with High School Calculus and Linear Algebra as pre-requisites for this course

At Metana we have 3 pillars of success. 

1. Curiosity. Ask questions and keep them coming.

2. Consistency. We will closely monitor your GitHub contributions so do NOT try to cram assignments at the last minute. That would never work out well for you.

3. Feedback. Don’t be scared to ask questions or give feedback. Google can’t always explain exactly what you don’t understand. We have a low instructor-to-student ratio specifically to facilitate more communication.

We appreciate student feedback and continuously improve our curriculum based on it.

This changes from week to week. It can be anything between 5 to 35 hours per week and will greatly depend on what’s covered that week and your level of expertise.

We want our students to succeed. So we recommend you reserve at least 20 hours per week for this course. Some weeks might take more hours than others.

In addition to being a bootcamp, we also work as a recruiting firm, and we get paid a commission if we help you find employment. Therefore, we are very invested in you finding a job.

We won't necessarily offer you a job off the bat either. We will work with you to enhance your online presence and make your resume look good. The hiring process is incredibly random, and any successful job search requires submitting numerous applications and acting professionally while doing so.

Yes, You'll improve not only in your job but also in the code you write for it thanks to Metana!

Imesh is a Data Scientist by profession who is current working as a Consulting Analyst for McKinsey & Company. His expertise in the field of data science is exceptional and has contributed heavily to build the curriculum.

 

Yes!, We've made sure to integrate progressive learning into our AI/ML bootcamp. Start off with Data analytics and become a natural with the fundamentals also become a Metana certified Data Analyst!

Only if you are able to pass our machine learning phase evaluation. It is much more competent and advanced than our analytics bootcamp. But you can surely take it after you complete our data analytics phase in the AI/ML bootcamp.

  1. For this course, you must have 1-2 years of experience developing Javascript-based production software or one of its syntactical supersets, like TypeScript.
  2. Bash scripting will be used for a variety of tasks throughout this course, so a level of competence with any shell scripting language is a requirement for success.
  3. You also need to be familiar with Git and version control systems like GitHub.

This course is designed for programmers with at least 2 years of experience. 

Yes, However you need to be able to code in Python and a little experience in using Python libraries such as NumPy, Pandas etc.

Large classes tend people to communicate less which we want to avoid at all costs. We prefer a low instructor-to-student count to facilitate the answering of questions and asking of questions. This class size also makes it easier for the instructor to keep up with your progress, identify your weaknesses, and give you a personalized learning experience. 

We want to concentrate on providing a quality service first and then focus on growing our company. 

As our testimonials say, this bootcamp is really hard. There is a chance that you will be unable to complete it within the given 16 weeks. With this course, we are trying to condense 2+ years of skill and experience into a period as short as 4 months. During this time, you will constantly learn and make new and lasting connections. 

We recommend you check whether you can keep aside 20 to 30 hours per week for 16 weeks to complete this program. If you are somewhat of a slow learner or have relatively less experience, this bootcamp may end up taking all your time. So be prepared for the chance of this becoming your full-time bootcamp.

Of course, we know that the internet is saturated with content and resources. But the real question is, do you know exactly where to begin?

At Metana, we will guide you along a clear roadmap. Time is money. If you cluelessly wander about the internet for useful resources, you will be wasting your time.

If you like us, value your time and would like to be assured that you are taking the best path possible, this bootcamp is for you. We will ensure you don’t waste any time searching for resources. You will not have to scroll for hours on Reddit forums or StackOverflow. All the necessary resources will be at your fingertips.

That is completely fine. As long as you are showing interest and doing the work, we will consider your reasons for taking more time. 

However, we’ve taken the utmost care when creating this program and therefore, we expect our students to prioritize this course and take it seriously. 

We understand that sometimes, life gets in the way. Things happen and you might have to delay your education. We take these situations on a case-by-case basis and will consider moving you to our next cohort. However, if we notice that you are falling behind because you are not taking it seriously, we will ask you to leave the program. 

Our main goal with this program is to equip you with skills to have successful careers in the field of blockchain. But it is up to you to have the passion and interest for this field. 

As part of the application process, you will schedule a 30-minute video interview with a student admissions officer. In the three days leading up to the interview, you must complete and pass a coding test with a sufficient score. If your interview is successful, you will receive a conditional offer of acceptance. To secure your place in the program, you must pay at least the first month's tuition.

Our program has seen success with self-taught programmers who work as freelancers. This experience often allows for more flexibility in completing course assignments.

Additionally, a strong passion for learning is key to success in this program, as we focus on staying up-to-date with the latest technologies.

Prior experience with low-level programming languages such as C or C++, as well as having a graduate degree, may also increase the likelihood of success in this program.

Ultimately, the most successful students are those who are highly curious and eager to acquire new knowledge. Our bootcamp aims to streamline the learning process by providing targeted and relevant information, allowing students to focus on mastering new skills through practice

Lectures and study materials at Metana may include both in-house resources and high-quality materials sourced from the internet. These resources may include readings or video content.

While lectures are an important part of the learning process, we believe that hands-on practice is key to truly understanding and retaining the material. Therefore, we try to minimize the amount of time spent in lectures and focus more on problem-solving and working on projects.

During lectures, we make an effort to cover the less obvious or unexpected aspects of the topics being studied.

We started metana in February 2022 and our first bootcamp on June 2022.

Still have a question? Send us an email at [email protected]

Applications for our next cohort close in:

Start Your Application

Secure your spot now. Spots are limited, and we accept qualified applicants on a first come, first served basis.

The application is free and takes just 3 minutes to complete.

What is included in the course price?

Expert-curated curriculum

Weekly 1:1 video calls with your mentor

Weekly group mentoring calls

On-demand mentor support

Portfolio reviews by design hiring managers

Resume & LinkedIn profile reviews

Active online student community

1:1 and group career coaching calls

Access to our employer network

Job Guarantee

Check Your Eligibility.