A data science course is designed to equip students or aspiring data scientists with the knowledge and skills required to analyze and interpret comple...Read more

Helix Tech

Helix Tech

Helix Tech

  • Hands on Training
  • Flexible Timings
  • Industry Based Training
  • Experienced Experts
  • Affordable Fees
  • Placement Opportunities

Attend a Free Demo

Fill the details and we will call you for further guidance


Our Facts and Figures

Welcome to the organization where the results speak louder than their words


Student Placed




Companies TieUp


Industry Courses

Get 100% Job Placement by enrolling in Certified Training Course

Enter Your Details Now
Key Highlights

Limited Students Batch

Personalised Attention

Highly Qualified Experts

Flexible Batch Timings

Interactive Learning

Live Projects

Career Support

Job Oriented Training

Students Placed and Hired in Companies

Course Highlights


A data science course is designed to equip students or aspiring data scientists with the knowledge and skills required to analyze and interpret complex data to extract valuable insights and make data-driven decisions. These courses typically cover a wide range of topics in statistics, programming, machine learning, data visualization, and data management. Here's an overview of what you might expect in a data science course. Students learn how to acquire, clean, and preprocess data to prepare it for analysis. This involves dealing with missing values, outliers, and data inconsistencies. Fundamental statistical concepts and probability theory are covered to understand data distributions and make inferences from data.


Join Our Free Upcoming Webinar


At Helix Tech IT Services Inc, we believe that the success of a company is rooted in the talents and aspirations of its employees. We are committed to creating a positive impact on the tech industry by bridging the gap between top tech talent and companies while empowering job seekers to achieve their career aspirations. We believe in creating a thriving ecosystem where technology and innovation comes to life.


Course Curriculum

  • Introduction to Data Science & Evolution of Data Science
  • Difference between Data analyst & Data Scientist
  • Roles & Responsibilities of Data Scientist
  • Difference between Supervised & Unsupervised learning
  • What is machine learning
  • Deep learning and Artificial Intelligence
  • Probability
  • Bayesian Inference
  • Hypothesis testing
  • Descriptive Statistics
  • Inferential Statistics
  • Hypothesis testing
  • Statistical Distribution(Discrete and continuous)
  • Installation of Anaconda Framework
  • How to work with Jupiter notebook and Spyder IDE’s
  • Python Data type
  • What is linear regression?
  • What is logistic regression?
  • Difference between Linear and Logistic
  • Difference between Regression and Classification
  • Building a model using Linear and Logistic Regression
  • What is clustering?
  • Difference between K-means and KNN
  • Different Use cases of clustering
  • Building a model using K-means and KNN
  • Data Exploration and Cleaning
  • Optimization Techniques
  • Natural Language Processing (NLP)
  • Data Wrangling
  • Time Series Analysis
  • Big Data Processing
  • Model Deployment
  • Data Ethics and Privacy
  • Descriptive and Inferential Statistics
  • Classification
  • Data Ethics and Privacy
  • Data Storytelling
  • Data Science Tools
  • Domain Knowledge
  • Ensemble Methods
  • A/B Testing

Professional Certificate

Beginner level

No previous experience necessary

Course Session

20 Days 1 Hours per day

Flexible schedule

Learn at your own pace

Course Key Features

Data scientists are in high demand across various industries, making it a lucrative career choice

You'll learn how to make informed decisions based on data analysis, leading to better business outcomes

Skills Covered
  • Data Analysis
  • Statistics
  • Machine Learning
  • Data Visualization
Job Roles
  • Data Scientist
  • Machine Learning Engineer
  • Big Data Engineer


The training is designed to describe the main goals and objectives of the training, such as enhancing skills, improving knowledge, etc.
This training is intended for specify the target audience, such as beginners, professionals, specific job roles, etc.
List any required prerequisites, such as prior knowledge, experience, or skills that participants should have before taking the training.

Interview Question

Data Science combines statistics, maths, specialised programs, artificial intelligence, machine learning etc. Data Science is simply the application of specific principles and analytic techniques to extract information from data used in strategic planning, decision making, etc. Simply, data science means analysing data for actionable insights.
Logistic regression measures the relationship between the dependent variable (our label of what we want to predict) and one or more independent variables (our features) by estimating probability using its underlying logistic function (sigmoid).
The Dimensionality reduction refers to the process of converting a data set with vast dimensions into data with fewer dimensions (fields) to convey similar information concisely.

Latest Blogs

We are committed to keeping our candidates up with the ongoing job-searching environment and the services we provide, so our blogs reflect that

07 Jan 2024
Artificial Intelligence - Shaping the Future | Helix Tech ..

Discover the potential of Artificial Intelligence, its applications, and how it's changing the world. Explore its benefits and challenges. Helix Tech Inc - Your AI partner.

07 Jan 2024
10 Proven Strategies to Boost Your Organic Website Traffic..

Unlock the potential of your website with these 10 SEO-friendly strategies to increase organic traffic. Improve user experience and rankings for lasting success.

27 Jun 2024
Empower Your IT Career: Helix Tech IT Services - Your Trus..

Discover how Helix Tech IT Services, the best IT staffing agency in the USA, can empower your career and help you land a job with Fortune 500 companies. Get expert guidance and flexible job opportunities.