Advanced Program in Data Science

Elevate your career with our comprehensive 6-month Advanced Program in Data Science, certified by Acacia University. This professional development program equips you with in-demand skills in Python programming, data analytics, machine learning, and AI implementation through 80 hours of live instructor-led training.

6 Months

5 Modules

4 Assignments

Online Learning

3 Projects

Intermediate

Globally Recognized & Accredited:

15000

Students Trained Globally

25

Industry-Aligned Programs

70

Countries with Active Alumni

87

Career Transition Success

Tools & Technologies That Power Success

Master the complete data science ecosystem with hands-on experience using industry-leading tools and frameworks. Our Advanced Program in Data Science equips you with practical skills in Python programming, data manipulation, visualization, and machine learning – preparing you for real-world data challenges.

Python

MySQL

learn anaconda

Anaconda

Jupyter Hub

Pandas

NumPy

Seaborn

Matplotlib

Excel

GIT

HTML

CSS

Tools & Technologies That Power Success

Master the complete data science ecosystem with hands-on experience using industry-leading tools and frameworks. Our Advanced Program in Data Science equips you with practical skills in Python programming, data manipulation, visualization, and machine learning – preparing you for real-world data challenges.

Python

MySQL

learn anaconda

Anaconda

Jupyter Hub

Pandas

NumPy

Seaborn

Matplotlib

Excel

GIT

HTML

CSS

Acacia University Professional Development

Acacia University Professional Development has initiated various programs in partnership with Airtics Education. The wide range of programs aims to upskill millions of students in trending technologies through a blend of theoretical and hands-on knowledge and are taught by leading academicians.
Airtics Education’s Advanced Programs are offered as part of Acacia University Professional Development Programs, and the learners are certified by the University.

Course Modules

Python Basics and Core Concepts
Python Basics and Core Concepts

Learn fundamental Python programming including variables, data types, conditional statements, loops, and functions. Master the building blocks essential for data science applications.

Essential Python Libraries
Essential Python Libraries
Explore NumPy for numerical computing, Matplotlib for data visualization, and Pandas for data manipulation. Gain hands-on experience with the most important data science tools.
Practical Programming Skills
Practical Programming Skills
Develop the ability to write efficient Python scripts for data analysis. Practice with real-world examples and build confidence in problem-solving using code.
Learning Outcomes
Module Summary Duration: 4-6 weeks

By completing this foundational module, you will:

  • Master Python programming structure and learn how to write efficient programs for data analysis
  • Understand core Python concepts including syntax, functions, and conditional statements for problem-solving
  • Acquire essential Python skills to transition into specialized branches like Machine Learning and Data Science
  • Gain proficiency with key libraries (NumPy, Pandas, Matplotlib) to write scripts for data manipulation and analysis
Mathematical Foundations
Mathematical Foundations

Master linear algebra, probability theory, statistics, and statistical tools. Build the mathematical foundation required for advanced data analysis and machine learning algorithms.

Data Formats & Tools
Data Formats & Tools
Learn to work with CSV files and Excel spreadsheets. Understand different data formats and how to efficiently import, export, and manage data across various platforms.
Data Cleaning & Preparation
Data Cleaning & Preparation
Develop skills to identify and fix data quality issues including incorrect, corrupted, duplicate, or incomplete data. Master data preprocessing for reliable analysis.
Learning Outcomes
Module Summary Duration: 3-4 weeks

By completing this module, you will:

  • Master statistical tools for working with datasets effectively
  • Learn the essentials of probability and statistics for data analysis & visualization
  • Know how to import and clean data using libraries like NumPy and Pandas for data exploration and analysis
  • Learn to fix incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset
Pandas Mastery & Data Frames
Pandas Mastery & Data Frames

Explore the Pandas library fundamentals and learn to create data frames and series. Master the essential tool for data manipulation and analysis in Python.

Data Collection & Selection
Learn systematic approaches to data collection and discover how to select specific data using Pandas. Master data filtering and extraction techniques.
Data Processing Techniques

Master data cleaning, standardization, and normalization processes. Learn to transform messy data into clean, analysis-ready datasets using industry best practices.

Learning Outcomes
Module Summary Duration: 3-4 weeks

By completing this module, you will:

  • Explore the basic understanding of Pandas library – Develop your programming skills with fundamental tools
  • Discover how to use pandas to streamline data cleaning and pre-processing
  • Learn how to create data frames and series in pandas
  • Analyze the process of collecting, cleaning, and pre-processing data
  • Learn how to select data using Pandas
scikit
Machine Learning Fundamentals

Master supervised and unsupervised learning concepts using Scikit-learn. Learn data modeling techniques and discover predictive relationships in datasets through hands-on practice.

Version Control & Development

Learn Git Version Control System (VCS) for managing code and collaborating on projects. Master essential development workflows for data science and machine learning projects.

Model Deployment & WebView
Build and deploy machine learning models using HTML/CSS for web interfaces. Learn to create interactive WebViews to showcase your data science projects.
Learning Outcomes
Module Summary Duration: 4-5 weeks

By completing this module, you will:

  • Learn about training data and how to use datasets to discover potentially predictive relationships
  • Understand basic concepts and common tools used in machine learning
  • Master machine learning techniques, including supervised and unsupervised learning with hands-on modeling
  • Learn the basics of HTML/CSS and Git version control system (VCS)
  • Build and deploy a model to enable WebView functionality
scikit
Unsupervised Learning Mastery
Deep dive into unsupervised learning algorithms including clustering and association techniques. Learn to discover hidden patterns in data without labeled examples.
ML Model Deployment
Master the art of deploying machine learning models into production environments. Learn integration strategies for organizational decision-making processes.
Hybrid Model Development

Learn to innovatively blend supervised and unsupervised models for enhanced performance. Master techniques for tracking and interpreting deployed models.

Learning Outcomes
Specialization Duration: 2-3 weeks

By completing this specialization, you will:

  • Understand the significance of carefully defining the problem before choosing a technique
  • Learn how to get data ready for unsupervised algorithms in particular
  • Explore options for integrating unsupervised models into the organization’s decision-making process
  • Discover how to innovatively blend supervised and unsupervised models for improved performance
  • Learn to interpret and track your unsupervised models for ongoing development

Your Success Story Starts Here

Every image here tells a story of transformation, dedication, and success. Be the next to wear the cap and gown. Enroll today, and let your journey begin.

Student Reviews

Every student has a story—of ambition, of challenge, of growth. In their own words, they share how Airtics became a turning point in their learning journey and helped them move closer to their goals.

Real-World Capstone Projects

Apply your data science skills to solve real business challenges through hands-on projects. Choose from our curated capstone projects or bring your own organizational problem to create a portfolio that showcases your expertise to future employers.

 

House Rental Predication

Build a machine learning model to predict house rental prices using market data, property features, and location analysis.
 

Image Classification

Develop a computer vision system using deep learning to automatically classify and categorize images.
 

Business Insights Reporting

Create interactive business dashboards that transform raw data into actionable insights and visual reports.

Learn from Industry Leaders & Experts

Learn from the best in the field. Our faculty combines academic brilliance with industry expertise, featuring PhD holders, senior data scientists, and AI researchers from top organizations.

Ms. PIYALI MONDAL - B&W
Ms. Piyali Mondal Head of Department
Ms. Priti Mondal - B&W
Ms. Priti Mondal Associate Faculty
Dr. Abdullah El Nokiti - B&W
Dr. Abdullah El-Nokiti Professor
Dr. Meraj Inamdar - B&W
Dr. Mohd Merajuddin Inamdar Professor
Dr. Madhavi Vaidya - B&W
Dr. Madhavi Vaidya Professor
Dr. Poonam Chaudhari - B&W
Dr. Poonam Chaudhari Professor
Dr. Anup Maurya - B&W
Dr. Anup Kumar Maurya Professor
Dr. Milan Joshi - B&W
Dr. Milan Amrutkumar Joshi Industry Expert
Dr. Mohamed Elhaw - B&W
Dr. Mohamed Elhaw Industry Expert
Dr. Pradeep Tiwari - B&W
Dr. Pradeep Tiwari Industry Expert
Global Student Community

Students from 60+ Countries Worldwide

Frequently Asked Questions

Find answers to common questions about our Advanced Program in Data Science. Learn about program details, requirements, and what to expect from this 6-month certification course.
Why should I join the Data Science program?
Data science isn’t just the way of the future, it’s the way of right now! It is being adopted in all sorts of industries, from health care to route planning, marketing & sales to banking industries and beyond. Even industries such as retail that you might not associate with big data are getting on board. Data science is the fuel of the 21st Century.
What if I fail to attend the classes?
We provide you with live recorded classes of the same session to follow up if you end up missing the same.
How does Data Science differ from Big Data and Data Analytics?
Each of these technologies complements one another yet can be used as a separate entity. Big Data refers to any large and complex acquisition of data. Extracting meaningful information from data is why Data Analytics is used for. While Data Science is a multidisciplinary field that aims to produce broader insights.
What can I expect from the Data Science program?
Accelerated data science career guidance with world-class training on the most in-demand data science and machine learning skills. Training and hands-on experience with key tools and technologies including Python, PowerBi, and concepts of Machine Learning. Upon completing the program, you will be receiving an international certificate from Acacia University Professional Development (AUPD).
Who can join the program?
Aspirants and professionals who are having basic computer programming skills can enroll for the program.
Do I need prior experience in coding to learn the program?

Basic knowledge of programming logic and technology exposure will be helpful.

What are the current capabilities of Artificial Intelligence (AI)?
Google Duplex can make phone calls to make restaurant and hair appointments. Google Deep Mind won a global Starcraft game challenge against gaming pros. Amazon uses AI for book and product recommendations. Websites are using chatbots to answer basic customer queries. Airports are using image recognition for staff security. Rolls Royce is using AI for predictive maintenance and servicing of airplane engines. Informatica is using AI for compliance and data gathering and analysis purposes. Fintech is using AI to combine and analyze more diverse datasets. In healthcare, AI can help analyze more data for preventative medicine. Baidu in China is producing self-driving buses for large cities.
What is the future of Artificial Intelligence (AI)?

Automated transport, taking over dangerous jobs, robots working with humans, improved elderly care, cyborg (organic/bio-mechanic) organisms, environment monitoring and response to climate change goals.

What is TensorFlow?
TensorFlow is an end-to-end open-source platform for Machine Learning (ML). It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.
Can a data analyst become a data scientist?
Yes. Many data analysts go on to become data scientists after gaining experience, advancing their programming and mathematical skills, and earning an advanced degree.‎
Should I study Data Analytics or Data Science?
Which you choose is largely a matter of preference. If you’re mathematically minded and enjoy the technical aspects of coding and modelling, a data science degree could be a good fit. On the other hand, if you love working with numbers, communicating your insights, and influencing business decisions, consider a degree in data analytics. Whether you study data science or data analytics, you’ll be building skills for an in-demand, high-paying career. ‎
How tough is deep learning?
The technical skills and concepts involved in machine learning and deep learning can certainly be challenging at first. But if you break it down using the learning pathways outlined above, and commit to learning a little bit every day, it’s possible. Plus, you don’t need to master deep learning or machine learning to begin using your skills in the real world.‎
Is Machine Learning a good career?

Yes. The average base pay for a machine learning engineer in the US is $123,608, as of April 2022. According to a December 2020 study by Burning Glass, demand for AI and machine learning skills is projected to grow by 71 per cent over the next five years. The same study reports a $14,175 salary premium associated with these skills.

Still have questions?

If you have any other questions or need further information about our Advanced Program in Data Science, don’t hesitate to contact us. Our admissions team is here to help you take the next step in your data science career.

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