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Data Science with Python Course with Placement in Chennai

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Data Science with Python Training in Chennai


ACTE Training Institute in Chennai, provides Best Data Science with Python Training in Chennai. The course will introduce the students to the basics of the python programming environment, including how to download and install python, expected fundamental python programming techniques, and how to find help with python programming questions.

In addition to this, the course will also brush up with data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Data frame as the central data structure for data analysis. The outcome of the course ends with a statistics primer, showing how various statistical measures can be applied to pandas Data frames.

By the end of the Data Science with Python Course in ACTE, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analysis.

Our Data Science with Python course fee is best value for money and tailor-made course fee based on the each student's training requirements. ACTE conducts Data Science with Python Institute with Placement in Chennai on weekdays training classes, weekend training classes, evening batch classes according to the learners flexibility with limited number of students in each batch.

ACTE helps you to learn Data Science with Python Course from beginner level to advanced techniques that is taught by experienced working professionals to get the placement in good MNC companies as quickly as once you complete the Data Science with Python certification training course.

Who Can Join Data Science with Python Institute in Chennai?

Python programming is the core technology that powers big data, finance, statistics and number crunching with English like syntax. The recent growth of the rich Python data science ecosystem with multiple packages for Machine learning, natural language processing, data visualization, data exploration, data analysis and data mining is resulting in Pythonification of the data science community. Today, Python data science language has all the nuts and bolts for cleaning, transforming, processing and crunching big data. So anyone who is interested in growing their career in any of the field mentioned above can do Data Science with Python Training Course in Chennai ACTE Training Institute.

Data Science with Python Training in ACTE
Placement
Placement

ACTE Training Institute Advantages in Chennai:

  • Practical oriented training has been provided by our institute so that the students can get better understanding of the concept.
  • Convenient lab facilities and excellent infrastructure.
  • Training has been undergone by the qualified and professional experts.
  • The syllabuses are based on the current trends and industry standards.
  • The training will be provided from basic level to the advanced level and tailor-made course fee based on the each student's training requirements.
  • Affordable fees and flexible timings.
  • Placement training will be provided for the candidates to get into their desired career.

Prerequisites for getting Data Science with Python Training in Chennai:

  • Learner of python course must have computer working knowledge.
  • Student should have interest to learn, Rest we take care till you get Champion in Business Analytics.
  • Should have the knowledge of object oriented programming concepts.
  • There are not any explicit stipulations to be told however basic information in any of the artificial language are extra a worth advantage.

DataScience with Python Training Course syllabus

Introduction to Data Science

  • 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

Python: Essentials (Core)

  • 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 & Customize Settings
  • 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
  • Simple plotting
  • Control flow & conditional statements
  • Debugging & Code profiling
  • How to create class and modules and how to call them?

Scientific distributions used in python for Data Science

  • Numpy, scify, pandas, scikitlearn, statmodels, nltk etc

Accessing/Importing and Exporting Data using python modules

  • Importing Data from various sources (Csv, txt, excel, access etc)
  • Database Input (Connecting to database)
  • Viewing Data objects - subsetting, methods
  • Exporting Data to various formats
  • Important python modules: Pandas, beautifulsoup

Data Manipulation – cleansing – Munging using Python modules

  • Cleansing Data with Python
  • Data Manipulation steps(Sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type conversions, renaming, formatting etc)
  • Data manipulation tools(Operators, Functions, Packages, control structures, Loops, arrays 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)

Data Analysis – Visualization using Python

  • 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)
  • Important Packages for Exploratory Analysis(NumPy Arrays, Matplotlib, seaborn, Pandas and scipy.stats etc)

Basic statistics & implementation of stats methods in Python

  • 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
  • Important modules for statistical methods: Numpy, Scipy, Pandas

Python: Machine Learning -Predictive Modeling – Basics

  • 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 )

Machine Learning Algorithms & Applications – Implementation in Python

  • Linear & Logistic Regression
  • 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)
  • Important python modules for Machine Learning (SciKit Learn, stats models, scipy, nltk etc)
  • Fine tuning the models using Hyper parameters, grid search, piping etc.

Project - Consolidate Learnings:

  • Applying different algorithms to solve the business problems and bench mark the results

Course Highlights

  • Free demo classes.
  • Free Wifi with Excellent lab facility and latest study materials.
  • Innovative ideas are taught by the professionals and best ideas with career development planning.
  • 100% placement Assurance.
  • Expert trainers will teach the students.
  • IT training in all tools & technologies.
  • Real-time Job support (Technical Support project level).
  • Excellent Resume & Interview preparation is done.
  • If you missed any class backup Classes Available.

About Trainer

  • 5+ experienced
  • Certified trainer
  • Working in top MNC company
  • Friendly and interactive
  • Trained more than 3000 students
  • Ready to help students - 24/7
  • Strong knowledge and perfect delivery
  • On the spot doubt clarifying person

John Victor
(amazon india Pvt Limited)
5+ experience

Certifications

  • DataScience with Python Certification
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