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Skill up – Start a career in data.

You are not too late to climb the latest tech tide👀✨

Zero to Metana DataVista

Skill up and learn coding



6-8 Weeks​

Course Duration


Time Commitment

4.8 Star

Rating on Course Report


Data Vista is your gateway to the data analytics domain, specifically designed for beginners with no prior coding knowledge or data skills. In just 6-8 weeks, this comprehensive course equips you with all the fundamental concepts and skills you need to embark on your journey into the world of data. Whether you’re aspiring to join our full Data Analytics Bootcamp or just curious to explore the data domain on your own, Data Vista provides the perfect foundation. Our easy-to-follow, hands-on approach will empower you with the essential knowledge, from data basics to key data analytics tools and techniques. With Data Vista, you’ll have the confidence to navigate the fascinating world of data and pursue your data-driven ambitions.




Week 1: Excel on Cocaine (Thinkcell)Introduction to Excel, creating tables, and basic functions.
Data lookup and filtering, using IF & SUMIF functions.
Creating charts and graphs in Excel.
Advanced Excel features.
Printing tables and Excel best practices.
Week 2: PythonIntroduction to Python and data types.
Working with loops and conditional statements.
Python libraries: pandas and numpy.
Functions and defining your own functions.
Python classes and object-oriented programming.
Week 3: PythonAdvanced data manipulation in Python.
Real-world data analysis and hands-on projects.
Building data analysis skills with Python.
Week 4: SQLIntroduction to databases and SQL.
Setting up a local database.
Writing basic SQL queries.
Filtering and manipulating data in SQL.
Implementing CRUD functionality in SQL.
Week 5: SQL applicationsAdvanced SQL techniques and merging tables.
Real-world SQL applications and projects.
Mastering SQL for data analysis.
Week 6: Version ControllingIntroduction to version control and Git.
Setting up and using Git for collaborative development.
Understanding GitHub and its features.
Hands-on experience with Git and GitHub for version tracking.



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.


We offer 2 options to get your career change started. 

Pay Upfront

$2,500  $2,000

Pay upfront & save up to 20% on tuition for a limited amount of time.

Amount Amount ( if enrolled in Data Analytics bootcamp)
Total tuition before discount $2,500 $2,500
Discount - $500 - $500
Data analytics bootcamp discount - $2,000
Paid at enrollment $2,000 -
Total tuition $2,000 $0

In 2 months


Pay monthly.

  Amount Amount ( if enrolled in Data Analytics bootcamp)
Data Analytics Bootcamp Discount - - $1,000
Paid at enrollment $1000 -
Monthly payments during course (2) $750 -
Estimated total tuition $2,500 $0

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.

Applications for our next cohort close in:

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

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

No data science experience? 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 aptitude 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 problem solving skill assessment test. (dates are available within 3-7 days from the application date)
  • You need to complete the 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.

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 mathematics.

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.

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.

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.


Only if you are able to pass our Data Analytics entrance evaluation. But you can surely take it after you complete our data analytics phase in the AI/ML bootcamp.

All you need is an aptitude for problem solving

Simple answer? Yes.
Honest answer? YES!

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.

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


Week Content
1. Introduction to Data Analytics

Types of data analytics
Steps in data analytics process
Importance of data analytics in business
Tools and software for data analytics
Overview of data collection and cleaning
Understanding data types and formats.

2. Data Collection and Cleaning Handling Missing Data
Handling Outliers
Data Types and Formats Analysis
3. Data Transformation and Integration Data Normalization
Feature Scaling
Data Integration Techniques
4. Data Reduction Techniques Principal Component Analysis (PCA)
Singular Value Decomposition (SVD)
Feature Selection
5. Descriptive Statistics and Data Visualization Measures of Central Tendency and Dispersion
Frequency Distributions
Box Plots, Histograms, and Scatter Plots
6. Hypothesis Testing and Correlation Analysis Types of Hypothesis Testing
Correlation and Causation
Pearson Correlation Coefficient and Spearman’s Rank Correlation Coefficient
7. Linear and Multiple Regression Simple and Multiple Linear Regression
Residual Analysis
Model Selection Techniques
8. Logistic Regression and Time Series Analysis Binary and Multinomial Logistic Regression
Stationarity and Time Series Decomposition
ARIMA and Seasonal ARIMA
9. Advanced Regression Techniques Ridge and Lasso Regression
Elastic Net Regression
Polynomial Regression
10. Classification Techniques K-Nearest Neighbors (KNN)
Naive Bayes
Decision Trees and Random Forests
11.Clustering Techniques K-Means Clustering
Hierarchical Clustering
Density-Based Clustering
12. Association Rule Mining and Market Basket Analysis Apriori Algorithm and Market Basket Analysis
Collaborative Filtering
13. Support Vector Machines (SVM) Kernel Functions
Non-Linear SVM
SVM for Regression
14. Neural Networks and Deep Learning Perceptron and Multi-Layer Perceptron
Convolutional Neural Networks (CNN)
Recurrent Neural Networks (RNN)
15. Evaluation Metrics and Model Selection Confusion Matrix and Classification Metrics
Cross-Validation and Model Selection Techniques
Bias-Variance Tradeoff
16. Ensemble Methods Bagging and Boosting
Gradient Boosting
17. Data Visualization with Python
Types of Visualization
Choosing the Right Chart
Design Principles
18. SQL for Data Analysis Introduction to SQL
Selecting Data with SQL
Joins and Grouping
Advanced SQL Queries
19. Data Wrangling with Python Introduction to Python for Data Analysis
Data Wrangling with Pandas
Data Cleaning and Transformation
Data Aggregation and Pivot Tables
20. Big Data Technologies Hadoop and MapReduce
Spark and Spark SQL
NoSQL Databases

**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.