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Data Analyst Course

Job Oriented Intensive Program

Want to be a data analyst? Our 3-month Data Analyst course at Quality Thoughts is the ticket! Learn the basics of Python, stats, SQL, Excel, Advance Excel, Power BI, and more. Get ahead with your skills and land your dream job. Enroll yourself in the Data Analyst Course right away!

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Data Science Training Course Upcoming Batches

Date:

3rd, 7th, 17th, 24th October

Time

9:00 AM TO 06:00 PM

Program Duration:

110 Days

Learning Format:

Training

Course Curriculum

Date:

3rd, 7th, 17th, 24th October

Time

11:00 AM TO 06:00 PM

Program Duration:

110 Days

Learning Format:

JOIP/I&I

Course Curriculum

India’s #1 Software Training Institute

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Upgrade Your Data Skills: Become a Data Analyst Master

Discover the world of data today with Quality Thoughts. Our Data Analyst course builds capabilities that help you extract insights from data, make informed decisions, and drive business success forward.

Key Features That Make the Difference

Build a Complete Set of Data Analyst Fundamentals:

Core concepts in data analysis

Work on Real-World Projects:

Give ways to apply theoretical skills to actual projects

Group Learning Environment:

Opportunity to learn along with peers

Industry-based Case Study:

Real-time challenges faced and find out how to solve them.

Data Science Overview

Comprehensive Training

Key Skills for Your Success

Skills Covered

Training Skills

Offered Programs

Exclusive Training

JOB ORIENTED INTENSIVE PROGRAM (JOIP)​

INTENSIVE & INTERNSHIP PROGRAM (I&I)

Pre Requisites

  • Basic statistics and probability understanding
  • Familiarity with data cleaning and manipulation
  • Proficiency in Microsoft Excel
  • Understanding of programming basics (e.g., Python or SQL)
  • Strong problem-solving and analytical skills
  • Curiosity and passion for data-driven insights

Course Curriculum

  • Introduction to Jupyter Notebook
  • Getting Started with Data Science
  • Unix Introduction
  • Python Basics
  • Python Introduction
  • Python Data Structure: Lists and Arrays
  • Python: Conditions and Branching
  • Python: Functions and Methods
  • Python: Objects and Classes
  • Practice Questions in Python
  • Introduction to NumPy
  • Linear Algebra in NumPy
  • Seaborn, Matplotlib
  • Project 1: Satellite Image Data Analysis using NumPy
  • Introduction to Pandas
  • Introduction to Probability
  • Probability Distributions
  • Describing Distributions
  • Probability Distribution with Multiple Variables
  • Population and Sample
  • Point Estimate
  • Confidence Interval
  • Hypothesis Testing
  • A/B Testing
  • Derivatives
  • Optimization
  • Gradients
  • Gradient Decent
  • Optimization in Neural Networks
  • Newton Methods
  • System of Linear Equations
  • Elimination Method
  • Row and Row Reduced Echelon form
  • Vector Algebra
  • Linear Transformation
  • Determinants
  • Eigen Values of Eigen Vectors
  • Array
  • String
  • Linked List
  • Searching Algorithm
  • Sorting Algorithm
  • Divide and Conquer Acqu
  • Stack
  • Queue
  • Tree Data Structures
  • Graph Data Structures
  • Dynamic Program
  • Data Acquisition
  • Data Wrangling
  • Data Statistical Analysis, Grouping and Correlation
  • Model Development
  • Model Evaluation and Refinement
  • Getting started in scikit-learn with the famous iris dataset
  • Training a Machine Learning Model with scikit-learn
  • Comparing Machine Learning Models in scikit-learn
  • Data Science Pipeline: Pandas, Seaborn, and scikit-learn
  • Cross-Validation for Parameter Tuning, Model Selection, and Feature Selection
  • Efficiently Searching for Optimal Tuning Parameters
  • Evaluating a Classification Model: Confusion Matrix and ROC
  • Basic Plotting for Data Visualisation
  • Data Manipulation for Visualisation
  • 1D Data Analysis: Histograms, Boxplots, and Violin Plots
  • Project 2: Visualization of world GDP and carbon dioxide emission
  • Project 3: Using Folium Library for Geographic Overlays
  • Introduction to Power-Bi
  • Data Extraction Process
  • Data Transformations
  • Data Modeling and DAX
  • Data Visualization with Analytics
  • Power-Bi, Q&A & Data Insights
  • Simple Linear Regression
  • Multiple Linear Regression
  • Non-Linear Regression
  • Regression Methods
  • Ridge Regression and Lasso Regression
  • Linear Regression and Decision Tree Regression
  • Random Forest Regression
  • Logistic Regression
  • Decision Tree Classification
  • Random Forest Classification
  • Boosting Algorithms
  • Bagging
  • K- Nearest Neighbours Classification
  • Naive Bayes Classification
  • K-Means Clustering
  • Hierarchical Clustering
  • K-Means and Hierarchical Clustering on the same dataset
  • Density-Based Spatial Clustering of Applications with Noise (DB-SCAN) Support Vector Machines & Regression
  • Principal Component Analysis (PCA)
  • Applying Principal Component Analysis on Handwritten Digits Dataset
  • Market Basket Analysis
  • Evaluate the speed, runtime and memory dependencies of algorithmic models Parallel computing systems such as SISD (Single Instruction Single Data Stream), SIMD (Single Instruction Multiple Data Streams), MISD (MultipleInstructions Single Data Stream), MIMD (Multiple Instructions Multiple DataStreams)
  • How to use coding tools
  • Create, review and execute unit test cases Corrective and Preventive actions for problems and defects can improve future designs
  • Measure and Optimize performance of algorithm
  • Deployment of the Models
  • Why Choose Quality Thought

    100% Success Rates in the Placement for Skilled People

    A gate way to your🤔 Bright Future in the IT industry

    Connect with us for Life-changing opportunities

    Testimonials

    Quality Thoughts’s Data Analyst course is an absolute game-changer. I now feel confident about dealing with complex data sets and extracting meaningful information. That is quite a good training session, I feel

    Anjali Prakash

    The real-world projects as well as the hands-on labs proved very priceless. I gained practical experience that surely works on the job.

    Riya Dubey

    I found all the faculty members to be knowledgeable and quite supportive. They made the learning process fun and interesting.

    Manoj Kumar

    Counseling through career services is beneficial. I at last got my dream job as a data analyst. Thanks.

    -Preeti Sharma

    Key Facts Of Quality Thought

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    Job Oriented Intensive Program (JOIP)

    student oriented

    50000+ Students Trained

    students levels

    15000+ Students Placed at Different Levels

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    Training by Realtime Industry Experts

    Company

    Tie Up With 250+ Compaines

    bank

    Educated 15+ BPO & Back Office/Ops on IT Trends

    Certification

    • Course completion: Complete all lessons.
    • Submission of assignment: Submit all projects and assignments on time.
    • Certificate receipt: Obtain the certificate within one week.
    • Authenticity: Verify the authenticity of the certificate.
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    Frequently asked questions

    Data analytics is comprised of the process of working with large datasets to identify common patterns. Qualitative tools assist businesses in making the right decisions and therefore improving their efficiencies and competitiveness.

    It is not necessary. Most classes in data analytics are entry-level, and as a result, users will learn all the tools they require from day one.



    They include; Python, SQL, R, tableaus, and Excel. These are the tools for cleaning, manipulating, and analyzing data as well as data visualization.



    Thus, some of the job openings, created by the current AI development are data analyst, data scientist, business intelligence analyst, market research analyst, and the rest.

    Wages depend on the experience and location of the employee. Nevertheless, data analysts are often provided with rather generous salary jobs.

    Ready to get Data Science JOB?

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