Data Science – Basic Course
Earn a recognized Data Scientist certification to boost your career and work on real-world projects using industry-aligned tools
4.7
(35,000)
(35,000+ students enrolled)
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.
- Open book online test for certification
- 100% pass rate guaranteed.
- 100% job assistance
- Lifetime membership to Anexas Alumni group.
- Online Line Customer support 24*7.
Course Content
- 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
- Ndarray, Data types, Array Attributes, Indexing and Slicing
- Array manipulation, Binary operator, String Function
- Arithmetic, Statistical, Matrix, linear algebra, sort, search, countings
- Data manipulation, Viewing, selection, grouping, merging, joining, concatenation
- Working with text data, visualization, CSV, XLSX, SQL data puling, operations
- Statistics, Linear algebra, models, special functions, optimization
- Probability & Stats Applications
- 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
- [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 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 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
- 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
- Polynomial Regression
- Regularization methods
- Lasso, Ridge and Elastic nets
- Categorical Variables in Regression
- Logit function and interpretation
- Types of error measures (ROCR)
- Logistic Regression in classification
- 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
- 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 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
Lean Six Sigma Master Black Belt | CEO, Anexas Europe
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.
This course includes
- 45 hours of Live interaction
- Study materials
- Training recordings
- Certificate of completion
- Digital badge
- Community Access
Accredited By
View Certificate
Training options for Data Science Beginners Course
Self Paced Learning
Features
- 45 hours of Recorded Sessions for course completion
- Global recognition and Trained Data Scientist Certificate from Anexas Europe
- Lifetime access to course materials and videos
- 24*7 customer support
Online Live Training
Features
- 45 hours of course completion
- 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
Industry Projects For Data Science
FAQs
Everything you need to know about Data Science
Still have questions?
Can’t find the answer you’re looking for?
Please talk to our friendly team.
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.
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.
We have flexible payment options.Â
- You can make full payment.Â
- You can choose an installment. Pay a token amount during registration, and pay the remaining balance anytime before the course concludes.
Choose from multiple payment options at Anexas:
- Card payment
- Net Banking
- Cash
- UPI payments
- Tabby
We have an easy cancellation policy made easy!Â
- If you cancel your registration 72 hours before the training starts, a 10% administration fee will be deducted.Â
- 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.
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