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
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.
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.
Training Options
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: Contact enquiry@anexas.net
Weekend Batch: 17th September
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
Industry Projects
FAQ
Why Data Science?
Data Science is very much favoured in almost all industries today because of its vast usage in data analytics, predictions, statistical facts and figures and trends. Due to advancements in technology, the importance of Data Science has increased and will be more in the upcoming years. As a Data Scientist, you will have uncountable opportunities in different industries and almost all companies as it is multi-disciplinary and every industry will be in need.
Data Science is your own path to having your dreams come true as Data Scientists are needed not only just in every leading industry but also in leading cities in the world. Data Science is your coupon to get into top MNC companies. The career scope as a Data Scientist is infinite and it can only be fully utilized by learning and gaining expertise in the skills with our Data Science certification.
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?
According to recent research, a Data Scientist earns an average of $114,000 USD in the United States and 900,000 INR in India every year. Data Science is the most fruitful career option nowadays. Some common job roles are-
- Data Scientist
- Python Programmer
- Machine Learning Engineer
- Data Analyst
- Data Engineer
What is the focus of this course?
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.
Are examination fees included?
Yes. Once you pay the fees for the training, all the other costs, such as certification cost, examination cost, study material costs, tools and software costs, will be included and no extra charges will be levied.
What are the payment options available?
Anexas offers the following payment options:
- Card payment
- Net Banking
- Cash
Can I cancel my enrollment? Will I get a refund?
- If the cancellation is done by the delegate 72 hours before the start of the training, 10% will be deducted as an administration fee.
- If the cancellation is done by the delegate after that, no refund will be made.
- After making the payment, the delegate can postpone the training date and join another batch, without any additional charges.