Data Analytics Course

"Accelerate Your Career with Our Job Interview Guarantee. Open Doors to Limitless Opportunities Until You Achieve Your Dream Role."

Minimum Eligibility to Join
  • Engg. (All streams), BCA, BSC (Phys, Che, Maths, Stats, CS, IT), BBA, BCOM with Maths, BA Eco with Maths, MCA, MSC(IT), MBA, UGFY
  • X, XII and Grad ≥ 50%
Enroll Now
img

100 %

Job Assistance

10+

Years of Average Experience

120

Successful Projects Delivered

10K

Happy Students
Overview

Data Analytics Course Overview

This data analyst course will transform you into a data analytics expert. In this course, you will learn the latest analytics tools and techniques, how to work with SQL, the languages of R and Python, the art of creating data visualizations, and how to apply statistics and predictive analytics in a business environment.

  • Earn a recognized Data Analyst certification to boost your career
  • Learn SQL, R, Python, data visualization, and predictive analytics skills
img

Students Feedback

img
img
img
img
Discover Professional Courses Here

Professional Courses that follow the latest trends to enhance your career.

Mentorship
1 : 1 Mentorship

Personalized guidance between a mentor and mentee for focused skill development and learning support.

Live Projects
Live Projects

Ongoing real-world projects with deadlines, client-driven, hands-on, and collaborative for practical learning experiences.

Practical Experience
Practical Experience

Hands-on application of knowledge and skills in real-world situations, enhancing learning and expertise development.

Learn with

World-Class Curriculum

Mastering MS Excel and Concepts of Programing

This module helps you take your first steps towards becoming a successful Data Scientist. You will be introduced to the fundamentals of MS Excel, Learn about formatting concepts, formulas and Statistical Analysis using Excel, Learn the meaning and utility of algorithms, loops, and flow charts, Understand how computers, operating systems, and the World Wide Web works.

Topics Covered

  • Discovering MS Excel
  • Understanding Programming Basics
icon
Discovering Data Analysis

In this module you will learn how to store, manipulate, and retrieve the data along with the advanced visualisation techniques using Matplotlib, Seaborn and Plotly. You will master converting the raw data into high order operations and perform analysis using NumPy and Pandas.

Topics Covered

  • Discovering SQL Basics and mastering Data Analysis
  • Understanding Python for DS - Installation, Building Blocks, Strings and Data Structures
  • Grasping Python for DS - Functions, Modules, Files, Lambda functions, Errors and OOPs
  • Discerning Probability and Statistics - Descriptive Statistics, Distributions and Probability Theory
  • Mastering Probability and Statistics - Hypothesis Testing, Regressions and ANOVA
  • Grasping Data Preprocessing - Numpy, Pandas, RegEx
  • Discovering Data Preprocessing - Web Scraping and EDA
  • Mastering NoSQL
  • Discerning Data Visualization with Tableau
Understanding Machine Learning with Python

During this module you'll learn about linear algebra and calculus and their applications in Data Science, You'll also get a comprehensive understanding of Machine Learning, Linear Regression, Naïve Bayes and Support Vector Machine along with understanding the difference between Bagging and Boosting in Machine Learning.

Topics Covered

  • Grasping Machine Learning - Math for DS
  • Discovering Machine Learning - Linear Regression
  • Understanding Regularization Techniques - LASSO and RIDGE
  • Introduction to Classification and Logistic Regression
  • Discovering KNN, Naive Bayes and SVM
  • Mastering Decision Tree, Random Forest and Boosting
  • Grasping Unsupervised Learning - Clustering and PCA
Data Engineering

Discover the various elements of the Hadoop Ecosystem and how they can be used to solve Big Data problems. Understand how Relational Data Processing works in Spark and perform real-time Stream Processing using Apache Spark and with Amazon Kinesis. You will then get a thorough understanding of Spark SQL and Understand how to deploy Machine Learning models to make inferences using Amazon SageMaker.

Topic Covered

  • Grasping Big Data Processing with Hadoop
  • Discovering Streaming Big Data with Spark
  • Mastering Streaming Big Data with Spark
  • Mastering Machine Learning Model Deployment on Cloud

Tools Covered

  • Hadoop
  • Spark
  • AWS
NLP and Deep Learning

This module strengthen your fundamentals of Natural Language Processing (NLP) and provides the hands-on experience with TextBlob and then Spacy. You will be performing sentimental analysis and creating chatbots and gain in depth understanding of Deep Learning, TensorFlow, and how Neural Networks work. You will also gain the exposure of understanding the application of AI in the real world.

Topics Covered

  • Discovering NLP - Feature Extraction, Texblob, Spacy, Text Classification
  • Grasping NLP - Sentiment Analysis and Chatbots
  • Discerning Deep Learning with Keras and Tensorflow - Keras, Tensorflow and CNN
  • Mastering Deep Learning with Keras and TensorFlow, Adv CNNs, NLP and GANs

Tools Covered

  • Keras
  • TensorFlow
Data Structures and Algorithms, with Career Support

Explore the fundamental techniques of Algorithm Analysis, Linked Lists and Binary Trees. You will also learn about the Advanced Data Structures and how to analyze the Asymptotic Performance of Algorithms. Learn Algorithmic Design Paradigms and Methods of Analysis and Microservices Architecture and its Implications.

Topics Covered

  • Basic Techniques of Algorithm Analysis
  • Linked Lists and Binary Trees
  • Advanced Data Structures
  • Analyze the Asymptotic Performance of Algorithms
  • Algorithmic Design Paradigms and Methods of Analysis
  • Microservices Architecture and its Implications
CERTIFICATION

Get certified to become a pro!

  • Certification recognized in 300+ companies
  • Prove that your skills are certified to employers
Contact Us
Spartikal certificate

What Sets Us Apart

Spartikal certificate
Project-Based Learning
Hands-on, practical exercises designed to enhance your learning experience and reinforce the concepts covered in the course. These projects serve as crucial components in the learning journey, as they allow you to apply the knowledge and skills gained in real-world scenarios. Eg: Wikipedia Scraper, PubG Predictive Analysis, Spell Checker & many more.
24 X 7 Doubt Support
24 X 7 Doubt Support
A dedicated service provided with this course for free to help you overcome any doubt, at any time, and anywhere. So unleash your coding potential with confidence, as our Doubt Support service stands by your side!

Benefits of this service:

  • -Access to Expert TAs
  • Prompt Response
  • Tailored Guidance
  • :1 Video & On-Call Support & Much More

Now code with confidence, triumph over doubts, and level up your skills!

Recognised Certification
Recognised Certification

Boost your coding street cred! Excel in the tech landscape with our comprehensive course and prestigious certificates that open doors to endless opportunities.

Perks of our certificates:
  • Credible Validation
  • Continuous Relevance
  • Helps in Career Advancement
  • Lifetime Validity

So get ready to experience the transformative power of our certificate and showcase your excellence!

Spartikal certificate
Expert Mentors
With a passion for teaching, our mentor(s) sessions will provide tailored guidance to all the aspiring coders. Launch a successful tech career with their structured learning methods.

Why our mentors are the best:

  • Industry Expertise
  • Interactive Teaching
  • Student Friendly Approach

Gain the invaluable expertise they have to offer and become a proficient coder!

Data Science

Course Curriculum

Day 1-2: Introduction to Data Analytics

  • What is Data Analytics?
  • Importance and applications in various industries
  • Overview of the data analytics process

Day 3-4: Python Basics

  • Introduction to Python programming
  • Variables, data types, and basic operations
  • Control flow (if statements, loops)

Day 5-7: Python for Data Analysis

  • Introduction to Jupyter Notebooks
  • Libraries: NumPy and Pandas
  • Data manipulation with Pandas (Series and DataFrames)
  • Basic data cleaning and transformation

Day 1-2: Data Collection and Importing Data

  • Importing data from various sources (CSV, Excel, SQL databases)
  • Web scraping basics

Day 3-4: Data Cleaning and Preparation

  • Handling missing values
  • Data type conversions
  • Data normalization and standardization

Day 5-7: Exploratory Data Analysis (EDA)

  • Descriptive statistics
  • Data visualization basics (Matplotlib, Seaborn)
  • Identifying patterns and trends

Day 1-2: Data Visualization Techniques

  • Advanced plotting with Matplotlib and Seaborn
  • Interactive visualizations with Plotly

Day 3-4: Statistical Analysis

  • Introduction to statistical concepts (mean, median, variance)
  • Hypothesis testing and confidence intervals
  • Correlation and regression analysis

Day 5-7: Introduction to Machine Learning

  • Overview of machine learning concepts
  • Supervised vs. unsupervised learning
  • Basic algorithms: Linear regression, k-means clustering

Day 1-2: Data Analytics Project

  • Project selection and dataset exploration
  • Defining the problem statement

Day 3-5: Project Implementation

  • Data cleaning and preparation
  • Exploratory data analysis and visualization
  • Model building and evaluation

Day 6-7: Presentation and Reporting

  • Creating a compelling data story
  • Visualizing results effectively
  • Writing a project report and presenting findings

Course Duration Fee & Timing

Course Duration

Certificate Course in Data Science

1 Month

Course Fee

Total Course fee including GST

$1,999

Next cohort Starts

6th Aug, 2024

9:00 PM

Roles After This Course

Data Scientist

Avg. Salary: 14.4 LPA*

AI Engineer

Avg. Salary: 11.1 LPA*

AI Specialist

Avg. Salary: 20.3 LPA*

AI Consultant

Avg. Salary: 11.6 LPA*

Data Science Experts & More

Request a call back

Our experienced staff will call at a time that suits you, up to five working days in advance.

Apply Now
Have a Doubt?

Frequently Asked Question

Data science involves extracting insights from data using scientific methods and technology.

Data science skills include programming (Python, R), statistics, machine learning, data visualization, domain expertise, and communication.

Data science is applied in finance, healthcare, e-commerce, marketing, transportation, energy, and government sectors, among others.

This is the second item's accordion body. It is hidden by default, until the collapse plugin adds the appropriate classes that we use to style each element. These classes control the overall appearance, as well as the showing and hiding via CSS transitions. You can modify any of this with custom CSS or overriding our default variables. It's also worth noting that just about any HTML can go within the though the transition does limit overflow.

This is the second item's accordion body. It is hidden by default, until the collapse plugin adds the appropriate classes that we use to style each element. These classes control the overall appearance, as well as the showing and hiding via CSS transitions. You can modify any of this with custom CSS or overriding our default variables. It's also worth noting that just about any HTML can go within the though the transition does limit overflow.