Data science Basic – Anexas UAE

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Data Science – Basic Course

Earn a recognized Data Scientist certification to boost your career and work on real-world projects using industry-aligned tools

2 Live Projects

25+ worked out projects

1-1 Live Sessions

100% job assistance

4.7

(35,000)

(35,000+ Students enrolled)

This course includes

Accredited By

Course Description For Data Science Basic Course

Experience and learn concepts needed by data scientists. In this course, you will get the basic knowledge needed to start off your Data Science journey. You will understand what Data Science is and will learn different aspects of it. Upon completing this course, you will be able to prepare your data for analysis, perform basic visualization of data and model your data. All Anexas’s courses emphasize practicality and hence include many exercises and real-time projects.

What you'll gain

Internationally recognized certification from Anexas Europe
Interactive online live training with industry experts.
Lifetime dashboard access to course materials.
Project guidance with 25+ industry-based projects.
Real-time project completion.
Tools required for the training.

Course Content

Python

Installation – Anaconda, Pycharm, Virtualenv
Introduction to python
Basic Syntax, comments, Variables
Data Types, Numbers, Casting, Strings, Booleans
Operators, Lists, Tuples, Sets, Dictionaries
If…Else, While Loops, For Loops
Functions, Lambda, Arrays
Arrays, Classes/Objects, Inheritance, Iterators
Scope, Modules, Dates, Math, JSON
PIP, Try…Except, User InputP, String Formatting
File Handling, Read Files, Write/Create Files, Delete Files

Numpy

Ndarray, Data types, Array Attributes, Indexing and Slicing
Array manipulation, Binary operator, String Function
Arithmetic, Statistical, Matrix, linear algebra, sort, search, countings

Pandas

Data manipulation, Viewing, selection, grouping, merging, joining, concatenation
Working with text data, visualization, CSV, XLSX, SQL data puling, operations

Scipy

Basic Probability, Random experiments, Conditional Probability, Independent Events,
Bayes theorem, Permutation, combination
Random variable , Discrete/Continous RV, PDF, PMF, CDF
Joint Probability Distribution, Conversion techniques, EV, varience, SD
Covariance, Correlation, Chebyshev Inequality, Law of Large number
Central limit Theorem, Percent & Quantiles, Moments
Skewness & Kurtosis, Gaussian, Binomial, Standard Normal, Distribution
Poisson, Multinomial, Hypergeometric, Uniform, Exponential Distribution

Statistics

[Mean, median, mode ](Sample/population), Expected values, Variance, standard deviation
Sampling distribution, Frequency distribution, Estimation Theory
confidence interval, Maximum Likelihood Estimation
Hypothesis Testing – Chi-Square, Student’s T, F Distribution, Z test
Hypothesis Testing – Type-I, Type- II, p Values, Relationship between NULL & Alternative
Least Square Methods – Numerical

Data pre-processing

Data Cleaning – Handling Missing Values(Data Imputation), Dealing with Noisy data(Binning Technique)
Advance Data cleaning – Will be referred while Regression, clustering topics
Data Transformation Techniques- Normalization (minmax, log transform, z-score transform etc.), Attribute Selection, Discretization,Concept Hierarchy Generation
Data Reduction: Data Cube Aggregation, Numerosity Reduction, Dimensionality Reduction

Data visualization

Data Mapping, Charts, Glyphs, Parallel Coordinates, Stacked Graphs
Bar, Pie, Line Charts, bubbles, geo maps. Gauge, whisker charts, Heatmaps, scatterplots, plottings images, videos, motion charts, performing EDA
Building Dashboard – Live implementation – PowerBI

Linear regression

Implementation of Numerical intuitions
Regression basics: Relationship between attributes using Covariance and Correlation
Relationship between multiple variables: Regression (Linear, Multivariate) in prediction.
Residual Analysis: Identifying significant features, feature reduction using AIC, multi-collinearity

Multiple linear regression

Polynomial Regression
Regularization methods
Lasso, Ridge and Elastic nets
Categorical Variables in Regression

Non-linear regression

Logit function and interpretation
Types of error measures (ROCR)
Logistic Regression in classification

Clustering

Distance measures – euclidean distance
Different clustering methods (Distance, Density, Hierarchical)
Iterative distance-based clustering;
Dealing with continuous, categorical values in K-Means
Constructing a hierarchical cluster
K-nearest neighbours, K-Medoids, k-Mode and density-based clustering
BIRCH, DBSCAN, Mean Shift, Spectral Clustering, Gaussian Mixture Model

Association rule mining

The applications of Association Rule Mining: Market Basket, Recommendation Engines, etc.
A mathematical model for association analysis; Large item sets; Association Rules
Apriori: Constructs large item sets with mini sup by iterations; Analysis discovered association rules;
Application examples; Association analysis vs. classification
FP-trees
PageRank

Key Benefits of Data Science

Enhance your career with Data Science skills

Hone your problem-solving, analytical, and programming skills, and advance your professional skill set with a career in Data Science

Join the industry of your choice

Data Science tools and techniques are applicable across various industries, allowing you to choose and excel in the sector of your preference.

Internationally available opportunities

Get international opportunities. Data Science is a globally recognized field with high demand in organizations worldwide, opening doors to international career prospects.

Become an internal consultant or an adviser to your company

Achieve better job roles and higher salaries by becoming a certified Data Science professional, offering your expertise as an internal consultant or adviser in data-driven decision-making.

Deepen your business understanding

Data Science encourages you to think strategically and analytically, providing clear insights into business performance, trends, and opportunities through effective data analysis and modeling.

Get Project Management experience

The more you advance in Data Science, the more experience you gain in managing complex data projects, enhancing your professional credentials and expertise.

Learning from the Best trainer

Amitabh Saxena, CEO of Anexas Europe has done some great work in the quality domain. He has an experience of more than 33 years. He is also the founder of Anexas and will be your trainer for the course. He has consulted Fortune 100 organizations including ADNOC, Dell, SABIC, Aramco, Ministry of Health, DP World, Alfuttaim Motors, EMC2, Bank Muscat, TATA Business services, Deloitte , TATA motors finance ltd, Steel authority of India, Indian railway , Colgate Palmolive , Novartis, Novozymes Denmark, HP, Tech Mahindra, Reliance, Bharat Petroleum, Maersk ,Cisco and the list goes on.

Training options for Lean Six Sigma Green Belt

Self Paced Learning

Features

Online Live Training

Features

45 hours of course completio
Live interaction with instant query clarification
Continuous project guidance during the sessions
Global recognition and Trained Data Scientist Certificate from Anexas Europe
Lifetime access to course materials and videos
One free one-on-one session with renowned Master Black Belt Amitabh Saxena
Flexible timings

Corporate Training

Features

Customised course content and duration for your organisation
Company-specific training with company-related examples and case studies
Live interaction with instant query clarification with renowned Master Black Belt Amitabh Saxena
Project completion during the training
Data Science tools and techniques aligned to the organization

FAQs

Everything you need to know about Data Science

What is the focus of this course

Our comprehensive course will provide you with a deep understanding of Data Science and cover various aspects of this field. By the end of the course, you will gain the skills to effectively prepare and analyze data, create impactful data visualizations, and develop data models. Expand your knowledge and capabilities in Data Science with us

Is the examination fee included?

Yes. Once you pay the fees for the training, all the other costs such as examination costs, study material costs, tools and software costs, and project training costs will be included and no extra charges will be levied.

What are the payment plans?

We have flexible payment options.

You can make full payment.
You can choose an installment. Pay a token amount during registration, and pay the remaining balance anytime before the course concludes.

What payment options are available?

Choose from multiple payment options at Anexas:

Card payment
Net Banking
Cash
UPI payments
Tabby

Can i cancel my enrollment? Will i get refund?

We have an easy cancellation policy made easy!

If you cancel your registration 72 hours before the training starts, a 10% administration fee will be deducted.
Unfortunately, no refunds will be issued for cancellations made after that.
However, if you’ve already made the payment, you can reschedule your training to another batch at no extra cost. We value your convenience and strive to accommodate your needs.