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Data Science with Python
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Description

Data Science with Python Training at Apponix offers the best comprehensive methods for learning analytics in Bangalore. This training program has been curated with extensive inputs from the experts in the industry, aiming excellence with years of industry experience.  As a student, you will be able to learn various components and tools in Data analytics, Machine Learning algorithms and many more techniques to culminate valuable business insights. The Data analytics market is steaming up in India and the rest of the world because of the exponential rise of data being gathered. As the user base grows, the related data is being captured by the software & the businesses and they harness this data to forecast the consumer behaviour. For this job to be done perfectly, the consumer market offers immeasurable opportunities to skilled and certified Data Scientists to help them achieve their goals. The data analytics market is booming in our country and so is the demand for certified and professional data scientists. If you wish to be on the list, hurry and enrol for this course at Apponix as the seats are limited.

This particular course, Data Science with Python, is an instructor-led course with a mean batch size of ten students. Within the 60 hours of classroom, students will obtain the theoretical & practical knowledge/information about required skills. The trainer’s holistic approach is stemmed to satisfy the long-run wants of the scholar.  They facilitate 100% job/placement post the successful completion of the course & also provide the students with an option to take a demo class before enrolling for the course.

What will I learn?

  • Use Python for Data Science and Machine Learning
  • Use Spark for Big Data Analysis
  • Implement Machine Learning Algorithms
  • You will learn NumPy, Pandas and Matplotlib 

Specifications

  • Free Demo
  • 100% Placement Assistance
  • Interactive Learning
  • Missed Class Recovery
  • Certification by Institute
  • Instalment Facility
  • Interview Training

Introduction to Data Science

  •  Introduction ToDataScience
  •  Real Time UseCasesOfDataScience
  •  Who is a data scientist?
  •  Github Tutorial
  •  Skillsets needed for a data scientist
  •  6 Steps to take in 3 Months for a complete transformation to DataSciencefrom any other domain
  •  Machine Learning-Giving computers the ability to learn from data
  •  Supervised vs Unsupervised
  •  DeepLearning vs Machine Learning
  •  Link to get Free Data to Practice?
  •  Some Great self LearningDataScienceResources(Books, Tutorials,Videos, Papers)
  •  Software Installation

 

Python Programming

  •  Introduction To Python
  •  “Hello Python Program” in IDLE
  •  Jupyter Notebook Tutorial
  •  Spyder Tutorial
  •  Introduction to Python
  •  Variable,Operators,DataTypes
  •  If Else, For and While Loops
  •  Functions
  •  Lambda Expression
  •  Filter, Map, Reduce
  •  Taking input from the keyboard
  •  HANDS ON
  •  INTERVIEW QUESTION DISCUSSION

 

Python Advanced Topics

  • NumPy
  •  Create Arrays
  •  Array Item Selection and Indexing
  •  Array Mathematics
  •  Array Operation
  •  HANDS ON
  • Pandas
  •  Introduction to Pandas
  •  Series
  •  Series indexing and Selection
  •  Series Operation
  •  Introduction to Pandas
  •  Data Frames
  •  Data Collection from csv,json,html,excel
  •  Data Merging,Concatenation,join
  •  Group By and Aggregate Function
  •  Order By
  •  Missing Value Treatment
  •  Outlier Detection and Removal
  •  Pandas builtin Data Visualisation
  •  HANDS ON
  •  INTERVIEW QUESTION DISCUSSION

 

Visualisation-matplotlib, seaborn

  •  Line Plots
  •  Scatter Plots
  •  Pair Plots
  •  Histograms
  •  Heat Maps
  •  Bar Plots
  •  Count Plots
  •  Factor Plots
  •  Box Plots
  •  Violin Plots
  •  Swarm Plots
  •  Strip Plots
  •  Pandas BuiltinVisualisation Library
  •  HANDS-ON
  •  INTERVIEW QUESTION DISCUSSION

 

Statistics

  •  Descriptive vs Inferential Statistics
  •  Mean,Median,Mode,Variance,Std. dev
  •  Central Limit Theorm
  •  Co-Variance
  •  Pearson’s Product Moment Correlation
  •  R - Square
  •  Adjusted R-Square
  •  Spearman’s. Rank order Coefficient
  •  Sample vs Population
  •  Standardizing Data(Z-score)
  •  Hypothesis Testing
  •  Normal Distribution
  •  Bias Variance Tradeoff
  •  Skewness
  •  P Value
  •  Z-test vs T-test
  •  The F distribution
  •  The chi-Square test of Independence
  •  Type-1 and Type-2 errors
  •  Annova
  •  HANDS ON
  •  INTERVIEW QUESTION DISCUSSION

 

Introduction to Machine Learning

  •  Introduction to Machine Leaning
  •  Machine Learning Usecases
  •  Supervised vs Unsupervised vs Semi-Supervised
  •  Machine Learning process Workflow
  •  Training a model
  •  Validating results
  •  Overfitting vs Underfitting
  •  Ordinal vs Nominal data
  •  Structured vs unstructured vs semi-structured data
  •  Intro to sci-kit learn
  •  HANDS-ON

 

Supervised

  • Regression
  • Regression Vs Classification
  • Linear regression
  • Multivariate regression
  • Polynomial regression
  • Multi-Colinearity,
  • Autocorrelation
  • Heteroscedasticity

 

Hands-On

  • Classification
  •  KNN
  •  Svm
  •  Decision Tree
  •  Random Forest
  •  Performance tuning of Random Forest
  •  Naive Bayes
  •  Overfitting Vs Underfitting
  •  Hands-On

 

Validation

  •  Classification Report
  •  Confusion Report
  •  ROC
  •  RMSE
  •  MSE
  •  Cross validation
  •  Hands-On
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Mr. Sreedhar

  • 8+ years of Experience in Data Science, currently spearheading the efforts.
  • Trained more than 2000+ students on Data Science at Apponix.
  • 5-star rating from all Data Science students.
  • Well versed in Data Science.
  • Excellent training delivery skills with an ability to present information well.
  • Demonstrable experience of being student focused and completing projects to hit deadlines and targets.
  • Demonstrable proof of enthusiasm, initiative, creativity and problem solving.
  • Demonstrable experience in delivering quality training on Data Science.
  • Excellent practical experience.

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Description

Data Science with Python Training at Apponix offers the best comprehensive methods for learning analytics in Bangalore. This training program has been curated with extensive inputs from the experts in the industry, aiming excellence with years of industry experience.  As a student, you will be able to learn various components and tools in Data analytics, Machine Learning algorithms and many more techniques to culminate valuable business insights. The Data analytics market is steaming up in India and the rest of the world because of the exponential rise of data being gathered. As the user base grows, the related data is being captured by the software & the businesses and they harness this data to forecast the consumer behaviour. For this job to be done perfectly, the consumer market offers immeasurable opportunities to skilled and certified Data Scientists to help them achieve their goals. The data analytics market is booming in our country and so is the demand for certified and professional data scientists. If you wish to be on the list, hurry and enrol for this course at Apponix as the seats are limited.

This particular course, Data Science with Python, is an instructor-led course with a mean batch size of ten students. Within the 60 hours of classroom, students will obtain the theoretical & practical knowledge/information about required skills. The trainer’s holistic approach is stemmed to satisfy the long-run wants of the scholar.  They facilitate 100% job/placement post the successful completion of the course & also provide the students with an option to take a demo class before enrolling for the course.

What will I learn?

  • Use Python for Data Science and Machine Learning
  • Use Spark for Big Data Analysis
  • Implement Machine Learning Algorithms
  • You will learn NumPy, Pandas and Matplotlib 

Specifications

  • Free Demo
  • 100% Placement Assistance
  • Interactive Learning
  • Missed Class Recovery
  • Certification by Institute
  • Instalment Facility
  • Interview Training
₹30,000 ₹ 30,000

Hurry up!! Limited seats only

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