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fundamental

Introduction to GitHub Actions

Math for Machine Learning

Introduction to Docker

Introduction to Git and Version Control

Data Visualization with Python

Data Wrangling with Python

Data Governance

Excel Fundamentals

Introduction to Linux

SQL Fundamentals

Python Fundamentals

Intermediate

AI Automation

GCP Fundamental

Introduction to Kubernetes

Data Visualization with Power BI

Data Visualization with Tableau

Azure Fundamental

AWS Fundamental

Introduction to NLP

Introduction to Computer Vision

Machine Learning

advanced

Introduction to Large Language Model

Introduction to MLOps

Big Data for Data Science

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Gain hands-on experience by working on real client projects, allowing you to apply your skills to solve actual business problems.
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Career Guides >

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LEARNING TRACK

Data Science Track

Intermediate

Online

Self-paced

This track concludes with practical skills in cloud computing, leading to end-to-end projects that prepare you to deploy data science solutions in a professional environment.

About the Track

Embark on your Data Science journey with the Data Science Track, designed for beginners and those aiming to advance their skills. This track begins with foundational knowledge in SQL and Python, covering essential database management, queries, data wrangling, and visualization. You’ll then explore Machine Learning (ML) and Deep Learning (DL) fundamentals, applying ML models to real-world challenges in Computer Vision (CV) and Natural Language Processing (NLP).

Top data skills program voted by students and partners

Courses in this track

SQL Fundamentals

Fundamental

By the end of this course, participants will be able to:

Grasp the core principles of relational databases and SQL syntax.
Effectively design, create, modify, and manage databases and tables.
Perform basic and advanced SQL queries for data retrieval and manipulation.
Utilize functions, aggregations, and conditional logic to conduct complex data analyses.
Apply window functions to uncover data trends and patterns.
Implement SQL in real-world applications, such as marketing analytics & risk management.

Python Fundamentals

Fundamental

By the end of this course, participants will be able to:

Comprehend Python syntax and foundational programming concepts.
Effectively use data structures and perform file operations.
Implement control flow statements to create logic-driven programs.
Design and use functions to promote code reusability and modular programming.
Apply object-oriented programming principles to design and implement classes.
Handle exceptions to build robust, error-resistant Python applications.

Data Wrangling with Python

Fundamental

By the end of this course, participants will be able to:

Work with Pandas Series, DataFrames, and Index objects
Read, write, filter, and transform structured data using Pandas
Clean data to ensure quality and integrity, including handling missing values and outliers
Reshape, pivot, and organize data for effective analysis
Merge, join, and group datasets using core data manipulation techniques
Apply data wrangling skills to real-world problems through hands-on projects

Math for Machine Learning

Fundamental

By the end of this course, participants will be able to:

Demonstrate proficiency in key statistical distributions and utilize them effectively in real-world applications
Apply appropriate sampling techniques and interpret the results
Conduct hypothesis testing using both basic and advanced methods
Perform vector and matrix operations relevant to machine learning
Optimize machine learning models using calculus-based technique

Machine Learning

Intermediate

By the end of this course, participants will be able to:

Understand and apply core machine learning concepts.
Leverage mathematical principles to solve machine learning problems and perform exploratory data analysis.
Preprocess and transform data through cleaning, feature engineering, and dimensionality reduction.
Implement, validate and optimize machine learning models. Explore advanced applications.

Introduction to NLP

Intermediate

By the end of this course, participants will be able to:

Explain the architecture and working principles of transformers and attention mechanisms.
Implement transformer encoders and decoders from scratch.
Develop and fine-tune large language models like BERT and GPT for various NLP tasks.
Evaluate and deploy LLMs effectively in real-world applications.
Utilize RAG techniques to enhance the capabilities of LLMs in information retrieval and generation tasks.

Introduction to Git and Version Control

Fundamental

By the end of this course, participants will be able to:

Understand the fundamentals of Git and version control systems.
Manage local Git repositories and track changes effectively.
Collaborate on projects using GitHub and remote repositories.
Apply advanced Git techniques for collaboration using GitFlow and GitHub Flow.

Big Data for Data Science

Advanced

By the end of this course, participants will be able to:

Explain the key principles of cloud computing and describe the core AWS services for compute, storage, data streaming, and machine learning.
Set up, configure, and manage AWS EC2 instances to run scalable and flexible cloud applications.
Use Spark and EMR to process and analyze large datasets through distributed computing, and perform data operations using Spark DataFrames.
Develop, train, and deploy machine learning models using AWS SageMaker, and apply them in real-world scenarios.
Use AWS services like Athena, Quicksight, and Boto3 to create end-to-end data pipelines that enable querying, analyzing, and visualizing data

Introduction to MLOps

Advanced

By the end of this course, participants will be able to:

Understand MLOps principles, Python tools, and the ML pipeline lifecycle.
Use Ray, SageMaker, MLflow, and DVC for training, tracking, and versioning.
Package models with Pickle/ONNX and manage features with modern data tools.
Deploy models using serverless tech and build CI/CD pipelines.
Monitor model performance, detect drift, and automate retraining.
Explore LLMOps workflows, prompt engineering, and RAG pipelines.

Advanced SQL for Data Science

Coming Soon

Machine Learning Use Cases

Coming Soon

This Learning Track include:

Multiple courses in one track — build skills step by step
Engaging video lessons + hands-on quizzes
Capstone projects to strengthen your skills
Certificate of Completion
Full access with your active subscription

Not the right path for you?

We also offer personalized and customized path that suits your learning and career goals. Talk to our advisors.

student success

What our graduates are saying

Pooja Sureja (2022 Alumni)

“Best Bootcamp!!”

I started my journey as a Mechanical Engineer. Making a career transition was hard decision to make. All the teachers and professors have played an important role shaping my professional career. Their care for the students’ well being and their ability to cater to all learning styles was one of the keys to my success. I would definitely recommend this program for all the career switchers. Awesome career service provider. Mentors are well educated and help a lot in resume building, interview preparation.

OUR ALUMNI ARE WORKING AT

Common Questions

Find answers to your questions about the Learning Track

What is a Learning Track?

A Learning Track is a curated series of courses, projects, and assessments designed to help you master a specific skill set or career path.

How is a Learning Track different from a single course?

Learning Tracks include multiple courses plus capstone or portfolio projects, offering a more comprehensive and structured learning experience.

How long will I have access to the Learning Track?

Access is tied to your subscription. As long as your subscription is active, you can continue learning.

Do I get hands-on projects?

Yes, each Learning Track includes hands-on labs and a final capstone project to build your portfolio.

Will I get a certificate?

Absolutely. Once you complete the entire Learning Track, you’ll receive a certificate of completion.

Still have questions?

If you have other queries or specific concerns about our Learning Track Subscription, don’t hesitate to let us know. Your feedback is important to us, and we aim to provide the best support possible.

Your Learning Journey Awaits 🚀

Grow your skills, build projects you’ll be proud of, and unlock new opportunities — all at your pace.

WeCloudData is the leading data science and AI academy. Our blended learning courses have helped thousands of learners and many enterprises make successful leaps in their data journeys.

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