Data Science – Basic Course
Industry-based projects with real-time completion
Interactive live session and doubt clearing
100% job assistance with interview and placement guidance
Data Science Basic Course Description
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.
Data Science Basic Course Benefits
- Interactive online live training with industry experts.
- Lifetime dashboard access to course materials.
- Content-rich study material.
- Free eBooks with worked out projects.
- Project guidance
- Real-time project completion during the training.
- Participants will be certified by ANEXAS Europe.
- A soft and hard copy of the certificate.
- International recognition.
- Learn from the best trainers.
- Tools required for the training.
- Open book online test for certification.
- 100% Pass rate guaranteed.
- Lifetime membership to Anexas Alumni group.
- Get a chance to win cashback benefits.
- Online Line Customer support 24*7.
100% Job Assistance
Anexas Data Science course comes with 100% job assistance. Learn Data Science with Anexas and advance your career with the most reputed Data Science job roles.
Benefits of Job assistance
- Get Placement guidance.
- Prep Interview skills with real-time industry-based Q&A.
- Learn Personality Development.
- Fill in any gap years in your experience.
- Gain from Anexas Internship program.
Eligibility criteria
- Complete at least basic and Intermediate level in Data Science course by Anexas.
- Fresher or Experienced, anyone can apply.
- Programmers or Non-programmers, anyone can apply.
Data Science Basic Training Options
Self Learning
- 45 hours of Recorded Sessions for course completion
- Training Certificate from Anexas Europe Certification (AEC)
- Lifetime access to study material
- Lifetime access to learning videos
Online Live Training
- 45 hours of course completion
- Live interaction with instant query clarification
- Continuous project guidance during the sessions
- Global recognition
- Trained Data Scientist (Basic) Certificate from Anexas Europe
- Access to learning videos
- Diverse training batch
- Flexible timings
Upcoming Batch
Weekday Batch: 19th May
Weekend Batch: Contact [email protected]
Data Science Basic Course Content
Module 1 - 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
Module 2- Numpy
- Ndarray, Data types, Array Attributes, Indexing and Slicing
- Array manipulation, Binary operator, String Function
- Arithmetic, Statistical, Matrix, linear algebra, sort, search, countings
Module 3- Pandas
- Data manipulation, Viewing, selection, grouping, merging, joining, concatenation
- Working with text data, visualization, CSV, XLSX, SQL data puling, operations
Module 4- Scipy
- Statistics, Linear algebra, models, special functions, optimization
- Probability & Stats Applications
Module 5- Probability
- 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
Module 6- 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
Module 7- 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
Module 8- 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
Module 9- 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
Module 10- Multiple Linear Regression
- Polynomial Regression
- Regularization methods
- Lasso, Ridge and Elastic nets
- Categorical Variables in Regression
Module 11- Non-linear Regression
- Logit function and interpretation
- Types of error measures (ROCR)
- Logistic Regression in classification
Module 12- 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
Module13- 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
Enquiry Form
Data Science Basic FAQ
Why Data Science?
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.
Who is your trainer?
- Total 7 years of experience in Data Science, Machine Learning, Deep Learning & Application Development.
- Contributed to 46+ Patents for different countries (US, China, Europe)
- Published research paper at the National Library of Medicine.
- Currently a mentor at the University of Texas at Austin.
- Serving as Senior Data Scientist.
What are the benefits of Data Science certification?
- High demand
- Infinite career opportunities
- Highest pay due to high exigency
- Recruited by top companies
- Flexibility to switch domains
- Opportunity to pursue self-career
What are the job roles that you can opt for after certification?
Data Science is a highly lucrative career option, with Data Scientists earning an average of $114,000 USD in the United States and 900,000 INR in India annually, as per recent research. Explore a range of rewarding job roles in the field:
- Data Scientist
- Python Programmer
- Machine Learning Engineer
- Data Analyst
- Data Engineer
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.
Are examination fees included?
Yes! Our training fees cover all associated costs, including certification, examination, study materials, and tools/software expenses. There are no additional charges, ensuring a hassle-free learning experience for you.
What are the payment options available?
At Anexas, we provide convenient payment options to suit your preference. Choose from the following methods:
- Card Payment
- Net Banking
- Cash
Can I cancel my enrollment? Will I get a refund?
Cancellation Policy:
If a delegate cancels the training 72 hours prior to the scheduled start, an administration fee of 10% will be deducted from the refund. However, if the cancellation occurs after this timeframe, no refund will be provided.
Rescheduling Option:
Once the payment is made, delegates have the flexibility to postpone their training date and join another batch at no extra cost. We aim to accommodate your schedule and ensure a seamless learning experience.
