Data Science with Specialisation in Artificial Intelligence and Machine Learning

A deep dive into the fundamentals of data science and machine learning with Python. You will gain comprehensive understanding and experience of the entire data science process from end-to-end, including data preparation, analysis and visualization, as well as how to properly apply machine learning algorithms to various situations or tasks. You’ll also work on a portfolio of projects that showcase your data science experience to potential employers.

overview

  • Data Science with Specialization in Artificial Intelligence and Machine Learning is a 4-month intensive course designed for individuals who want to gain expertise in the field of data science, machine learning, and AI. The course is designed to provide a comprehensive understanding and practical experience of the entire data science process from end to end.
  • Online AttendanceThe course begins with an introduction to Python programming language, which is widely used for data analysis and machine learning. You will learn the basics of Python syntax, data types, control structures, functions, and modules. You will also learn how to use Python libraries such as NumPy, Pandas, and Matplotlib for data manipulation, analysis, and visualization.
  • The course then moves on to cover the key concepts and techniques of data science, including data collection, data cleaning, data exploration, data visualization, and data analysis. You will learn how to use various statistical techniques to analyse data and make data-driven decisions.
    The course also provides a detailed understanding of machine learning algorithms, including supervised learning, unsupervised learning, and deep learning. You will learn how to apply these algorithms to various real-world problems such as classification, regression, clustering, and recommendation systems.
    In the specialization part of the course, you will gain in-depth knowledge of Artificial Intelligence and Machine Learning. You will learn how to design and develop AI and ML models using Python. You will also gain hands-on experience in developing neural networks and deep learning models using frameworks such as TensorFlow and Keras.
    Throughout the course, you will work on a portfolio of projects that showcase your data science, AI, and ML experience to potential employers. You will also get one-to-one mentorship and guidance from industry experts to help you succeed in your career.
    By the end of the course, you will have a comprehensive understanding of the entire data science process, machine learning algorithms, and AI concepts, along with hands-on experience in Python programming and various data science tools and techniques.

Course Objectives

  • Gain a comprehensive understanding and experience of the entire data science process from end-to-end
  • Learn to properly apply machine learning algorithms to various situations or tasks
  • Learn to prepare and analyze data, and visualize data effectively
  • Build a portfolio of projects that showcase your data science experience to potential employers

Package

300

Partner Job Openings

40

Highest Package

90

Placement Rate

course highlights

250+ Hours of Live classes encouraging interactive information flow

Fortnightly master class by industry experts

Hands on Training with Real World Data Sets

25+ One-to-One Sessions for Mentorship and Mock Interviews

Workshops for building your resume, LinkedIn & GitHub

750+ Practice Problems with Real Corporate Problems & Life Examples

Instant Doubt Support & Resolution

Course Curriculum

Module 1

  • Introduction to AI & its Applications
  • Relationship between Data Science (DS) and Machine Learning (ML)
  • Statistics Essential for DS
  • Programming Basics & OOPS concept
  • Data Structure & Arrays with Python for DS
  • Python Programming Fundamentals & Environment Setup-Anaconda

Module 2

  • DS with Python- Exploratory Data Analysis (EDA)
  • Computing with Python for DS- NumPy, SciPy, Sklearn
  • Data Manipulation with Pandas
  • NLP and Data Visualization in Python
  • Python Integration with Hadoop Map Reduce and Spark
  • Capstone Projects on DS with Python

Module 3

  • Machine Learning (ML)- Data Wrangling & Data Labeling
  • ML- Supervised Learning, Classification & Regression Algorithms
  • ML- Hypothesis Space & Inductive Bias Relation
  • ML- Unsupervised Learning & Clustering Algorithms
  • Deep Learning with TENSORFLOW & KERAS and Computer Vision Basics
  • Capstone Projects on ML & DL

Module 4

  • Introduction of Data Visualization/Analytics Tools
  • Data Visualization - Creating visualizations & Dashboards in Tableau
  • Capstone Projects using Tableau- Dashboards Creation
  • Data Visualization - Making Interactive Dashboards with PowerBi
  • Data Visualization - Making Interactive Dashboards with PowerBi
  • Business Analytics using Advanced Excel & VBA
  • Introduction of SAS Data Visualization

Module 5

  • Data Analysis using SQL- Database Design & Creation
  • Advanced SQL & Best Practices
  • Introduction of Big Data & Cloud Computing with AWS
  • Hadoop Architecture and Components
  • NOSQL Databases and MONGODB
  • SPARK & APACHE for Large Scale Data Processing

learning journey

  • When you join

  • During the program

  • Placements

  • Post Placement Support

  • Access to a World of Resources, Learning and the HM Community
  • Resume, Project Portfolio & LinkedIn Profile Development
  • Resume, Project Portfolio & LinkedIn Profile Development
  • Holistic Development with a focus on Practical Experience
  • Interview Preparation and Mock Interviews
  • Assessments and Final Certification from HM & NSDC
  • Curated Companies are Lined up
  • Support in Selecting & Applying for Roles
  • Role Specific 1-1 Mentorship to Maximise Selection Probability
  • Support in upskilling and growth on the Job
  • Access to Industry Experts and Mentors
  • Access to the HM Alumni Community & Opportunities

projects you will build

  • Analyse GDP of Countries

    NumPy in Anaconda and Google Collab (Logos for these 2 NumPy in Anaconda and Google Collab; Text only Analyse GDP of Countries)

  • Analyse Olympics Dataset

    NumPy in Anaconda and Google Collab

  • Analysing Ad Budgets for different media channels

    Machine Learning Scikit Learn in Anaconda and Google Collab

  • Analysing Cause of Death

    matplotlib in Anaconda and Google Collab

  • Display all the airports based in New York

    Python integration with Hadoop MapReduce and Spark in Anaconda and Google Collab

  • Analyse that a Book-My-Show URL is malicious prone via ML

    different Python libraries, features selection & machine learning classification models in Anaconda and Google Collab

  • Demand Forecast in Supply Chain and Retail via ML

    different Python libraries, Exploratory Data Analysis (EDA) & machine learning regression models in Anaconda and Google Collab

  • A user-based recommendation model for Amazon

    Python libraries, Exploratory Data Analysis (EDA), recommendation models & machine learning models in Anaconda and Google Collab

  • Designing a Sales dashboard for Ajio

    MS Excel

  • A Dashboard for Assessing Zomato's Performance

    Power BI

  • Gauge Agent Performance for Insurance Companie

    Power BI

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