Mastering Data Science for Managers
The Data Science certification course is designed for senior leaders and project managers to change their existing domains and start their careers as data science/analytics managers.

Monthly Recurring Batch

Program Duration

6 Months

Learning Format

Blended Learning

Program Fees


Course Overview

Data Science Certification Course for senior leaders, and project managers to Change Your Existing Domain and start their career as data science/analytics managers. This course will benefit you to master data science skills and will help you to handle interviews with more confidence if you are looking for a job in the data science domain.

Training Key Features

For More Information

    What you will learn

    About Acacia University Extension (AUX)

    AUX, an extension of the prestigious Acacia University, USA, 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.

    Upon completion of these programs, you will receive an Advanced Certification from AUX.

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    Skills Covered


    Machine Translation

    Sentiment Analysis


    Attention Models

    Word Embeddings

    Locality-Sensitive Hashing

    Vector Space Models

    Parts-of-Speech Tagging

    N-gram Language Models


    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

    Logistics and Delivery
    Web Search or Internet Web results
    Search Autocorrect and Autocomplete
    Customer segmentation
    Personalised Marketing
    Financial trading
    Marketing personalization


    Team managers, Project managers, Technical lead, professionals having 4 years and above of work exp. looking to start their career in data science & as an analytics manager.


    General Requirements:

    • No prior experience is required!
    • Basic computer skills like managing files, navigating the Internet, and running programs will be useful.
    • We’ll teach you everything you need to know, but the difficulty level of the projects may vary based on your familiarity with some of the content that is covered.
    • Successful completion of this program requires a commitment to stay on pace, complete projects, and finish the program within 3 months. See more details in the program FAQ.

    Hardware Requirements:

    • Computer running OS X or Windows

    Course Modules

    Topics Covered: Python, Probability and Statistics, Data Cleaning and Preprocessing, Introduction to Machine Learning, Unsupervised Machine Learning, ML Deployment

    • basics
    • conditional statements
    • loops lists
    • tuples
    • dictionaries
    • sets
    • functions
    • Hands on Numpy
    • Hands on Pandas
    • Exploratory data analysis, Matplotlib and Seaborn
    • Measures of central tendency and variation
    • Hypothesis testing (z-test, t-test)
    • Probability and distributions
    • Handling Missing values, outliers
    • One hot encoding, standization and normalization
    • Python ML pipelines
    • Supervised ML
    • Regression, Logistic regression, KNN
    • Decision Trees, Ensemble Learning (random forests)
    • Use case supervised learning
    • KMeans clustering
    • Hierarchical clustering
    • Use case unsupervised learning
    • Flask Framework
    • Integration/ Hosting an ML application

    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

      House Rental Prediction

      Image Classification

      Business Insights Reporting

      Career Support

      Frequently Asked Questions

      There are many kinds of roles, data scientist, analyst, data engineer and so on. There are many levels of companies. In smaller companies, the roles are usually combined into one while in larger companies there are more nuanced roles. Since more and more companies are just getting started on their data journey, the overall demand is expected to increase in the next few years.
      Hiring is going to slow down. First in small companies then eventually in enterprises in a couple of months. But it is likely to pick up in a few months. Hence, if you are looking to transition, this is a good time to ramp up skills and learn new things that might usually take some time.

      The following are some skills employers usually look for:

      • Should be good at coding
      • Should have good problem solving and analysis skills
      • Should be good with stats and building testing and deploying models

      A data scientist is a software developer ++ with stats and modeling skills to build and deploy models and make inferences from data.

      For more senior roles: People typically look for practical experience for several years or a specialized degree with some experience. Employers typically want folks who have seen various kinds of ML problems and solved them, who can come up with the right solution for a new problem when they are looking for a more senior role.
      For a beginner role: a degree usually adds some level of credibility, but if one has a good portfolio with good projects, it is usually an acceptable substitute. Employers do hope to see if the candidate is comfortable with basic concepts in ML along with being able to write code.

      The following three are the basic building blocks in terms of data science math background: Linear Algebra, Probability and Statistics and Calculus and optimization.

      Usually, the data science interview has a subset of these rounds.

      • Resume deep dive
      • ML Concepts
      • ML Scenario and Problem-solving
      • Algorithms and data structures
      • Coding
      • Behavioural

      Sometimes, some of these rounds might be combined, for instance, there might not be two separate rounds for coding and algorithms. Similarly, there might be a single round for ML concepts and scenario-based problem-solving.

      What is included in this course?

      I’m Interested in This Program

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        Course Preview

        Mastering Data Science for Managers

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