Advanced Program in Data Science
The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and Data Frame as the central data structures for data analysis.

Monthly Recurring Batch

Program Duration

6 Months

Learning Format

Blended Learning

Program Fees


Course Overview

By enrolling in the Advanced Program in Data Science offered under Acacia University Professional Development Programs (AUPD), you can gain valuable employment skills for in-demand positions in data science. This data science program is the perfect fit for students looking to advance their careers and benefit from a comprehensive, multidisciplinary approach.

Training Key Features

For More Information

    What you will learn

    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.

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    Skills Covered

    Python programming concepts

    Data Wrangling

    Data Visualization

    Mathematical Computing

    Model building and fine tuning

    Database management, SQL

    Supervised and unsupervised learning

    Business intelligence

    Exploratory Data Analysis

    Analytical Libraries

    Who Can Apply for the Course?

    Tools/ Frameworks/ Libraries

    Scripting tools

    Data science environment

    IDE shell

    Data Analytics Libraries

    Database Integrations

    Automated Machine Learning Models

    Supervised, Unsupervised

    Application And Use Cases

    Data Science in Sales And Marketing
    Future sales prediction, Price optimization
    Data Science in Supply Chain & Logistics
    Demand analytics
    Data Science in Manufacturing
    Actionable preventive maintenance
    Data Science in HR
    Predictive analytics


    This course is well suited for participants of all levels of experience because of the high demand for Data Science with Python programmers. Data Science with Python is beneficial for analytics professionals interested in Python, software and IT professionals interested in Analytics, as well as anyone with a genuine interest in Data Science.


    Good to have familiarity with basic concepts of mathematics and programming knowledge. Basic knowledge of Database tools and workflow will be a plus.

    Course Modules

    • Python basics
      • Variable and data types
      • Conditional statements
      • Loops
      • Functions
    • Python Libraries
      • Numpy
      • matplotlib
      • Pandas


    • Learning python structure and how to write programs in it
    • Basic concepts of Python, its syntax, functions, and conditional statements
    • Acquire the prerequisite Python skills to move into specific branches – Machine Learning, and Data Science
    • Understand packages to enable them to write scripts for data manipulation and analysis
    • Linear algebra
    • Probability
    • Statistics
    • Statistical tools
      • CSV
      • Excel


    • Introduce statistical tools for working with datasets
    • 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
    • Learning to fix incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset
    • Analysis library
      • Pandas
    • Data Collection
    • Data Cleaning and pre-
    • processing
    • Data Frames
    • Standardization
    • Normalization


    • 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
    • Supervised Learning
    • Unsupervised Learning
    • Data Modelling
    • Git Version Control System (VCS)
    • Build WebView


    • You will learn about training data, and how to use a set of data to discover potentially predictive relationships
    • Understand basic concepts and common tools used in machine learning
    • you will master machine learning techniques, including supervised and unsupervised learning and hands-on modelling, rounding out your artificial intelligence education
    • Learn the basics of HTML/CSS, and Git version control system (VCS)
    • Build and Deploy a model to enable WebView
    • Unsupervised learning
    • ML Deployment
    • Clustering
    • Association
    • Understanding the significance of carefully defining the problem before choosing a technique
    • How to get data ready for unsupervised algorithms in particular
    • Options for integrating unsupervised models into the organization’s decision-making process
    • How to innovatively blend supervised and unsupervised models for improved performance
    • Interpret and track your unsupervised models for ongoing development

    Interested in This Program? Secure your spot now.

    The application is free and takes only 5 minutes to complete.

      Student Reviews

      Veeraiah Yadav Doddaka
      IT Manager, Samsung

      I choose to learn Data Science and explored many options on which institute to join, among that what I found is Airtics as the best in terms of the course curriculum/on line content they designed and most…..

      Read More

      Prasad Joshi
      RF Optimization Engineer, Nokia

      I was a Data Science student at Airtics Education, which helped build a solid data science background and sharpen my programming skills…

      Read More

      Mohamed Hanan
      Procurement Assistant

      The program in Data Science offered by Airtics Education is rigorous and has provided me with a greater understanding of the data science world…

      Read More

      Capstone Projects

      Showcase your capabilities with real-world projects

      Bring Your Own Project
      Learn to solve a problem that you/your organization is facing using Data Science


      Choose From Curated Capstone Projects

      House rental Prediction

      Image Classification

      Business insights reporting

      Frequently Asked Questions

      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.
      We provide you with live recorded classes of the same session to follow up if you end up missing the same.
      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.
      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).
      Aspirants and professionals who are having basic computer programming skills can enroll for the program.
      Basic knowledge of programming logic and technology exposure will be helpful.
      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.
      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.
      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.
      Yes. Many data analysts go on to become data scientists after gaining experience, advancing their programming and mathematical skills, and earning an advanced degree.‎
      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. ‎
      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.‎
      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.

      What is included in this course?

      I’m Interested in This Program

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        Course Preview

        Advanced Program in Data Science

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