Data Science Online Training

Course Duration :
Learners : 1250
Reviews : 4.6

Make your dream come true as a Data Scientist by enhancing your skills through Data analytics, R programming, statistical computing, machine learning algorithms and so on by live use cases taught by certified professionals.

Data Science is one of the hottest jobs in the IT Industry. Data Scientist gets the highest package when compared to other people in the IT industry. A Data scientist does have good knowledge of python programming, Machine learning algorithms, Artificial Intelligence, and so on. Kits online training provides the best knowledge on Data analysis by live industry experts through Data Science Course.

What is Data Science?
Why Python for data science?
Relevance in industry and need of the hour
How leading companies are harnessing the power of Data Science with Python?
Different phases of a typical Analytics/Data Science projects and role of python
Anaconda vs. python
Overview of Python- Starting with Python
Introduction to installation of Python
Introduction to Python Editors & IDE’s(Canopy, pycharm, Jupyter, Rodeo, Ipython etc…)
Understand Jupyter notebook
Concept of Packages/Libraries – Important packages(NumPy, SciPy, scikit-learn, Pandas,
Matplotlib, etc)
Installing & loading Packages & Name Spaces
Data Types & Data objects/structures (strings, Tuples, Lists, Dictionaries)
List and Dictionary Comprehensions
Variable & Value Labels – Date & Time Values
Basic Operations – Mathematical – string – date
Reading and writing data
Control flow & conditional statements
Overview of Python- Starting with Python
Introduction to installation of Python
Introduction to Python Editors & IDE’s(Canopy, pycharm, Jupyter, Rodeo, Ipython etc…)
Understand Jupyter notebook
Concept of Packages/Libraries – Important packages(NumPy, SciPy, scikit-learn, Pandas,
Matplotlib, etc)
Installing & loading Packages & Name Spaces
Data Types & Data objects/structures (strings, Tuples, Lists, Dictionaries)
List and Dictionary Comprehensions
Variable & Value Labels – Date & Time Values
Basic Operations – Mathematical – string – date
Reading and writing data
Control flow & conditional statements
Importing Data from various sources (Csv, txt, excel, access etc)
Database Input (Connecting to database)
Exporting Data to various formats
Important python modules: Pandas
Cleansing Data with Python
Data Manipulation steps(Sorting, filtering, duplicates, merging, appending, subsetting,
derived variables, sampling, Data type conversions, renaming, formatting etc)

Python Built-in Functions (Text, numeric, date, utility functions)
Python User Defined Functions
Stripping out extraneous information
Normalizing data
Formatting data
Important Python modules for data manipulation (Pandas, Numpy, re, math, string,
datetime etc)
Introduction exploratory data analysis
Descriptive statistics, Frequency Tables and summarization
Univariate Analysis (Distribution of data & Graphical Analysis)
Bivariate Analysis (Cross Tabs, Distributions & Relationships, Graphical Analysis)
Creating Graphs- Bar/pie/line chart/histogram/ boxplot/ scatter/ density etc)
Basic Statistics – Measures of Central Tendencies and Variance
Building blocks – Probability Distributions – Normal distribution – Central Limit
Theorem

Inferential Statistics -Sampling – Concept of Hypothesis Testing
Statistical Methods – Z/t-tests (One sample, independent, paired), Anova,
Correlation and Chi- square
Introduction to Machine Learning & Predictive Modeling
Types of Business problems – Mapping of Techniques – Regression vs. classification vs.
segmentation vs. Forecasting

Major Classes of Learning Algorithms -Supervised vs Unsupervised Learning
Different Phases of Predictive Modeling (Data Pre- processing, Sampling, Model
Building, Validation)

Overfitting (Bias-Variance Trade off) & Performance Metrics
Feature engineering & dimension reduction
Concept of optimization & cost function
Concept of gradient descent algorithm
Concept of Cross validation(Bootstrapping, K-Fold validation etc)
Model performance metrics (R-square, RMSE, MAPE, AUC, ROC curve, recall, precision,
sensitivity, specificity, confusion metrics )
Segmentation – Cluster Analysis (K-Means)
Decision Trees (CART/CD 5.0)
Ensemble Learning (Random Forest, Bagging & boosting)
Artificial Neural Networks(ANN)
Support Vector Machines(SVM)
Other Techniques (KNN, Naïve Bayes, PCA)
Introduction to Text Mining using NLTK
Introduction to Time Series Forecasting (Decomposition & ARIMA)
Linear & Logistic Regression
Clustering using K means
Applying different algorithms
to solve the business

problems and bench mark

the results
Oracle Data Guard Broker: Features
Data Guard Broker: Components
Data Guard Broker: Configurations
Data Guard Broker: Management Model
Data Guard Broker: Architecture
Data Guard Monitor: DMON Process
Benefits of Using the Data Guard Broker
Comparing Configuration Management With and Without the Data Guard Broker

Self-Paced

  • Learn at your convenient time and place
  • Grab the practical exposure of the course through high-quality videos
  • Learn from basic to advanced level of the course led by real-time instructors

Online

  • Get a live demonstration of every topic by our experienced faculty
  • Get LMS Access of every session after the completion of the course
  • Gain the stuff to get certified

Corporate

  • Can enroll for Self paced, Live (or) the class mode of training
  • Engage in online training lecture by an industry expert at your facility
  • Learn as a full day schedule with discussions, exercises, and practical use cases
  • Design your own syllabus based on the project requirements
The trainer is a real-time expert and has a significant amount of technology
Irrespective of your class attendance, every session will be recorded. Soon after the completion of the class, you can able to access the videos
During the course, the trainer will provide the environment to execute the practical's.
Once you contact us, our support team will offer you great discounts.
Yes! we do accept the fee in installments, depending on the mode of training you take.
We offer the best training on different modes like self-paced, one-one, batch as well as corporate training.
Yes! Our support team will take your resumes and forward to the firms for placement assistance
During the course, the trainer will provide the probable certification question to make you certified.
03 November
18:30 PM
18 November
08:00 AM

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100% Online Course

Flexible Schedule

Beginner Level To Advance Level

Real-Time Scenarios With Projects

LMS Access

Interview Questions & Resume Guidelines Access