Artificial Intelligence (AI)
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What you will get when you take this course:
- World-class course content taught live by the expert Dr R Nageswara Rao.
- Zoom link for the class daily from course start to end date to your mail.
- Opportunity to clarify your doubts at the end of each class.
- Placement Assistance by posting available jobs, exclusively for Datatechs students.
- Certificate of Completion upon successful completion of the course.
Artificial Intelligence (AI) Syllabus
MODULE 1: PYTHON FOR AI
- Advantages of Python
- Python compiler and PVM
- Python instillation and environment
- strings
- char
- lists
- tuples
- range
- sets
- dictionaries
- if statement
- if…else statement
- if…elif…else statement
- while loop
- for loop
- break statement
- continue statement
- pass statement
- Array creation
- Array attributes
- 1D and 2D Arrays
- Matrix
- Built in and User defined functions
- Writing your own functions
- Importing functions
- Modules
- Packages
- Imports
- Series
- Dataframes
- Creation of dataframes from different sources
- Viewing data in dataframe
- Operations on dataframe
- Handling missing data
- Line plot
- Bar graph
- Pie chart
- Subplots
- Histogram
- Distribution plot
- Kde plot
- Count plot
- Box plot
- Scatter plot
- Sub plots
- Lmplot
- Pair plots
MODULE 2: MACHINE LEARNING IN AI
- One hot encoding using dummy variables
- One hot encoding using One hot encoder
- Simple Linear regression
- Multiple Linear regression
- Polynomial Linear regression
- Ridge regression
- Bias and Variance tradeoff
- Lasso regression
- Elasticnet regression
- Logistic regression
- Naive Bayes (Gaussian NB and Multinomial NB)
- KNN Classifier
- SVM
- Regularization
- Kernel Trick
- Decision Tree
- Entropy
- Gini Index
- Random Forest
- Conusion Matrix
- Bootstrapping, Bagging and Boosting
- K-Means Clustering
- Elbow technique
- Apriori Algorithm
- Selecting appropriate model for our data
MODULE 3: DEEP LEARNING IN AI
- Biological Neural Network
- Artificial Neural Network
- Perceptrons
- Layers of a Network
- Identity Function
- Binary step function or Threshold function
- Logistic function or Sigmoid function
- ReLU function
- Hyperbolic Tangent function
- Softmax function
- ANN
- ANN with Activation functions
- Variables
- Constants
- Placeholders
- Graph / Tensor / Session
MODULE 4: NATURAL LANGUAGE PROCESSING IN AI (NLP)
- Tokenization
- Stemming
- Lemmatization
- Stop words
- POS
- CountVectorizer
- Tf-idf Vectorizer