● Syntax and Semantics of Python programming
● Python History
● Versions of Python
● Features of Python
● Input and Output Functions
● Variable and Data Types
● What is a Variable
● Typecasting
● Data Types in Python
o Numeric
o String
o Boolean
o Compound
o List
o Tuple
o Set
o Frozen Set
o Dictionary
● Operators in Python
● Conditional Statements in Python
● Loops in Python
● User defined functions in python
● Strings in Python

● Creating arrays
● Array indexing
● Array slicing
● Numpy Data Types
● Copy vs View
● Array Shape
● Array reshape
● Iterating
● Join
● Search
● Filter
● Split
● Sort

● Pandas Series
● Pandas DataFrame
● Read CSV
● Read JSON
● Cleaning Data
● Missing Value Handling
● Optimizing Data Format
● Redundancy Minimization
● The corr() function
● Plotting Graphs in pandas

● Introduction to Data Analytics
● Brief history of Data Analytics
● What is Data Analytics?
● Why is Data Analytics important?
● What benefits does Data Analytics have?

● Text to Columns
● Concatenate
● Right with Concatenate
● Absolute Cell Reference
● Data Validation
● Time and Date Calculations
● Conditional Formatting
● Exploring Styles and clear formatting
● Using Conditional Formatting to hide details using the IF function
● pivot table
● pivot chart
● slicers
● creating charts

● MYSQL Server Basics
● Database models
● ER Model Overview
● Data types
● Understanding Test Database
● Basics Queries
● Removing Duplicates
● Data Filters Using Operators
● Data Sorting
● Grouping
● Joins
● Arithmetic and String functions
● Advanced Functions
● SET Operators
● Creating Complex Queries
● DML operations – Insert, Update & Delete

● Introduction to Power BI
● Report Visualization and Properties
● Chart and Map Report Properties
● Hierarchies and Drilldown Reports
● Power Query & M Language
● Power BI Cloud Operations
● Improving Power BI Reports
● Insights and Subscriptions
● Power BI Integration Elements

● High-Level overview of Data Science / Machine Learning project management methodology
● Random Variable and its definition
● Probability and Probability Distribution
● Balanced vs Imbalanced datasets
● Sampling Funnel, its application and its components
● Measure of central tendency
● Measure of Dispersion
● Expected value of probability distribution
● Measure of Skewness
● Measure of Kurtosis
● Various graphical techniques to understand data
● Installation of Python IDE
● Anaconda and Spyder
● Working with Python with some basic commands
● Normal Distribution
● Standard Normal Distribution / Z distribution
● Z scores and Z table
● QQ Plot / Quantile-Quantile plot
● Sampling Variation
● Central Limit Theorem
● Sample size calculator
● T-distribution / Student’s-t distribution
● Confidence interval

● Parametric vs Non-parametric tests
● Formulating a Hypothesis
● Choosing Null and Alternative hypothesis
● Type I and Type II errors
● Comparative study of sample proportions
● 2 Proportion test
● Chi-Square test
● Non-Parametric test
● Non-Parametric test continued
● Hypothesis testing using Python

● Scatter Diagram
● Correlation Analysis
● Principles of Regression
● Introduction to Simple Linear Regression
● R shiny and Python Flask
● Multiple Linear Regression
● Scatter diagram
● Ordinary least squares
● Principles of regression
● Splitting the data into training, validation and testing datasets
● Understanding Overfitting vs Underfitting
● Generalization error and Regularization techniques
● Introduction to Simple Linear Regression
● Heteroscedasticity / Equal Variance
● LINE assumption
● Multiple Linear Regression
● Model Quality metrics
● Deletion diagnostics

● Principles of Logistic Regression
● Types of Logistic Regression
● Assumption and Steps in Logistic Regression
● Analysis of Simple Logistic Regression result
● Multiple Logistic Regression
● Confusion matrix
● Receiver operating characteristics curve (ROC curve)
● Lift charts and Gain charts
● Lasso and Ridge Regressions
● Logit and Log Likelihood
● Category Baselining
● Modeling Nominal categorical data

● Supervised vs Unsupervised learning
● Data Mining Process
● Measure of distance
● Types of Linkages
● Hierarchical Clustering / Agglomerative Clustering
● Non-clustering
● Why dimension reduction
● Advantages of PCA
● Calculation of PCA weights
● 2D Visualization using Principal components
● Basics of Matrix algebra
● SVD – Decomposition of matrix data
● Definition of a network (the LinkedIn analogy)
● Measure of Node strength in a Network
● Introduction to Google Page Ranking

● What is Market Basket / Affinity Analysis
● Measure of association
● Apriori Algorithm
● Sequential Pattern Mining
● User-based collaborative filtering
● Measure of distance / similarity between users
● Driver for recommendation
● Computation reduction techniques
● Search based methods / Item to item collaborative filtering
● SVD in recommendation
● Vulnerability of recommender systems

● Sources of data
● Bag of words
● Pre-processing, corpus DTM and TDM
● Word Clouds
● Corpus level word clouds
● Semantic network
● Clustering
● Extract Tweets from Twitter
● Extract user reviews of the products from Amazon, Snapdeal and TripAdvisor
● Install Libraries from Shell
● Extraction and text analytics in Python

● Elements of Classification Tree – Root node, Child Node, Leaf Node, etc.
● Greedy algorithm
● Measure of Entropy
● Attribute selection using Information Gain
● Ensemble techniques
● Decision Tree C5.0 and understanding various arguments
● Random Forest and understanding various arguments
● Boosting / Bootstrap Aggregating
● AdaBoost / Adaptive Boosting
● Stacking
● Gradient Boosting
● Extreme Gradient Boosting (XGB)
● Artificial Neural Network
● Biological Neuron vs Artificial Neuron
● ANN structure
● Activation function
● Network Topology
● Support Vector Machines
● Classification Hyperplanes
● Best fit “boundary”
● Kernel Trick

● Introduction to time series data
● Steps of forecasting
● Components of time series data
● Scatter plot and Time Plot
● Lag Plot
● ACF – Auto-Correlation Function / Correlogram
● Visualization principles
● Naive forecast methods
● Errors in forecast and its metrics
● Model Based approaches
● Model-Based approaches
● AR (Auto-Regressive) model for errors
● Random walk
● ARMA (Auto-Regressive Moving Average), Order p and q
● ARIMA (Auto-Regressive Integrated Moving Average), Order p, d and q
● Data-driven approach to forecasting
● Smoothing techniques
● De-seasoning and de-trending
● Econometric Models
● Forecasting Best Practices
● Forecasting using Python

1. Iris Flowers Classification
2. Loan Default Prediction
3. Real Estate Price Prediction
4. Stock Price Prediction
5. Titanic Survival Classification
6. Breast Cancer Classification
7. Music Genre Classification
8. Fake News Detection
9. Credit Card Fraud Detection
10. Movie Recommender System

    Our Student Placed In These Companies

    Key Highlights

    40 Hrs Instructor Led Training

    40 Hrs Instructor Led Training

    22 Hrs Self-paced Videos

    22 Hrs Self-paced Videos

    56 Hrs Project & Exercises

    56 Hrs Project & Exercises



    Job Assistance

    Job Assistance

    Flexible Schedule

    Flexible Schedule

    Future Upgrade

    Future Upgrade

    Mentor Support

    Mentor Support


    Data Analytics Certification Course Brings Better Job Prospects

    Do you want to become a Data Analytics expert? It’s good to join a Data Analytics course and it helps you explore better job opportunities. We come up with the Data Analytics course that helps you get a clear idea of data ecosystem and we help you learn the fundamentals of data analytics. You will learn the importance of data gathering and data mining and it’s time to achieve success in real-time. Our data analytics course also gives you an idea of different roles of a Data Analyst and we help you achieve success in real-time.

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    We help you learn the details of the curriculum and once you are confident you can join the course. WE give you a clear idea of the benefits of joining Data Analytics training in Noida. The training program aids you learn how to deal with descriptive and inferential statistics. Also, you will get an idea of how to do regression analysis, data blending, data extraction, forecasting etc. You will even gain expertise in data visualizations and it’s time to explore a smarter form of technology. We assist you to enroll for the course and you can start attending the sessions.

    Time to Apply for Jobs

    We provide job placement support and thus you will explore better jobs. It’s time to complete the course successfully and we will help you apply for the best jobs.

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    Experienced Mentors

    Experienced Mentors

    APPWARS Technologies Pvt Ltd has highly-skilled & experienced mentors from Industry, proficient in their particular technologies.



    Stay sharp & focused with unlimited access to Coding Problems & Assignments during your training.



    Appwars Technologies Pvt Ltd is an MSME, Govt of India approved Company, and registered with the Ministry of Corporate Affairs.

    Live Interactive Session

    Live Interactive Session

    Get Live sessions from the comfort of your place with well-maintained quality & pace to make you understand better.

    Live Project

    Live Project

    Experience working on Real-time Projects to have in-depth, practical knowledge of your technology.

    100% Placement assistance

    100% Placement assistance

    With more than 1000+ Placement Partners. Get endless opportunities to get placed in these Small & Medium Companies

    Get Excellent Support

    We provide excellent support and it’s easy to speak to our representative. We will be happy to reveal the detailed curriculum and it helps you enroll for the course confidently. We are always here to give you better experience and you will comprehend the benefits of joining our Data Analyst course. We conduct the best Data Analyst training in Noida and it helps you give life a new start. We are one of the top institutes in Noida and we make it easy to apply for better jobs. We will clear all your doubts that make you feel confident to join our Data Analyst training program.

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    We will help you learn the course details and thus it becomes easy to join the training program. We are always here to make you aware of the syllabus and we come up with an industry-based curriculum. It helps you join a better job and thus you will achieve success in real-time. We motivate you to explore a better career and once you join our institute you will comprehend the importance of Data Analyst training program.

    And we also come up with regular assignments that help you gain good expertise. Our advanced lab features smarter equipment and here you will learn how to handle live projects. Finally, we bring the positive aspects that enable you to find the best Data Analyst jobs. 

    Data analytics training in Noida

    Top Reasons To Choose APPWARS Technologies

    • Data Analytics Training in Noida is conception as per the IT management standards.
    • APPWARS TECHNOLOGIES offers the best Data Analytics Training and devoted employment service in Noida with proper planned training courses.
    • Regular and weekend classes and assignments after each class are provided for Data Analytics Training in Noida.
    • Advanced lab designed with latest equipment.
    • Provide lab facilities to 24*7 and students are allowed to access the lab anytime.
    • One the best certified expert trainers or professionals having many years of real industry experience.
    • Mentors of Data Analytics Training in Noida helps in each type of project preparation, interview preparation and job placement support.
    • Giving personality development sessions including English spoken, mock interview, group discussion and presentation skills free of costs.
    • Providing free study materials, PDFs, video training, lab guides, exam preparation, sample paper and interview preparation.
    • Provide retake classes without any charges as often as you choose.
    • Helps the student to learn complex technical concepts.

    APPWARS Technologies Trainer for Data Analytics Training in Noida

    • TRAINER’S are expert and professional in their field of sphere and constantly boost themselves with new tools and technology to impart the best training for the real working environment.
    • Trainees have been carefully selected by our committee and recognized over the years by various organizations for their field work.
    • Trainees have many years of experience of working in big organization or institutes.
    • Certified trainers with at least 7 years of experience in IT Industries.
    • Trainees are connected with many placement cells of various companies to give support and help to the students for their placements.




    For queries, feedback & assistance



    For Call & WhatsApp

    +91- 9911169001


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    Placement Assistance After Data Analytics

    • APPWARS TECHNOLOGIES is a leader in apprehension placement assistance to the students with the help of an assigned placement cell.
    • The placement cell helps supports and assists the students during the time of placement.
    • APPWARS TECHNOLOGIES also provides best resume domicile service by helping the students to make their resume as per the latest industry trends.
    • APPWARS TECHNOLOGIES organize personality development sessions including group discussion, mock interview, and presentation skills on daily basis to help the students that they present themselves confidently.
    • APPWARS TECHNOLOGIES help the students to achieve their dream job.

    APPWARS Technologies Duration for Data Analytics

    • Regular Classes: 5 Days a week (Morning, afternoon and Evening)
    • Weekend Classes: (Saturday and Sunday)
    • Fast Track Classes also Available
    • One to One Classes also Available
    • Corporate Training also Available
    • Live Online Classes also Available

    People also ask

    APPWARS TECHNOLOGIES is one of the best for a data analytics institute in Noida.

    It can take anywhere from several months to several years to become a data analytics. The piece of time it takes you will trust on your present skill set, what type of educational way you choose, and how much time you spend each week developing your data analytics skills.

    In 2023, most businesses around the world view data analytics as a core part of their processes. With the ever-increasing quantity of data standing created, the need for prepared Data analyticss to analyze it is at an all-time high and will probably resume expanding in the coming years.

    Generally, data scientists expend hours in a stressful work atmosphere. Periodically, they work as a team and usually work independently. Usually, their working hours are elongated and analogized to traditional 9-5 job habits, specifically when working on a task or solving an issue to complete their task.

    What Does an Entry-Level Data analytics Do? The job duties of an entry-level data analytics include working to collect, managing, and analyzing data. In this employment, your commitments often rotate around completing an analysis of business or enterprise data to determine trends or assess implementation in a special sector.

    Evolving a data analytics isn’t difficult per se, though it does need certain technical skills that might be more challenging for some than others. Also, because of persisting improvements in the field, data analysis is a career way that needs continuing education.

    You must have a grade in any appropriate field and should have field knowledge in the area you are operating in. If you are from various sets but hope to become data analytics, it is feasible if you have the needed skill set.

    Very High Spirit represents the data found on a considerable number of the most delinquent salaries. Data analytics Salary in India varies between ₹ 1.5 Lakhs to ₹ 12.5 Lakhs with an average annual salary of ₹ 4.5 Lakhs. Salary estimates are based on 64.1k latest salaries acquired from Data analyticss.

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    Who can apply for the course?

    BE / BTech / MCA passed aspirants to make their careers as Web Developers / Data Scientists

    IT-Professionals who want to get a career as a Programming Expert

    Professionals from non-IT bkg, and want to establish in IT

    Candidates who would like to restart their career after a gap

    Web Designers for the next level of their career.


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